One may ask, why even evaluate a dream? If a successful venture is merely a dream, let us simply invest and hope for the best, or not invest and not wonder what might have been. For those interested in investing and understanding the rules that should be observed, we recommend reading. The prevailing view in the capital markets is that an understanding of a company’s value is a prerequisite to ‘fulfilling the dream’. Otherwise it could well turn out like a nightmare instead.

So how can one value a dream? Let’s first realise that dreams are not all created equal – start-ups come in a variety of shapes, shapes which evolve and hopefully grow.

• Let’s begin with pre-seed companies, the classic imagery evoked of a pre-seed company is two entrepreneurs sitting in a garage investing some money from FFFs (Friends, Family or Fools).
• Seed companies may find themselves in some kind of accelerator be in some kind of an accelerator or MNC hub like Google campus that supports the firm in financing, mentoring are or any other related aspects. Next level start-ups are post seed companies that are still private held doing their round A (capital raising of several M$), round B (capital raising up to 100M$) and round C+ of a similar amounts or higher than round D. Some start-ups will turn into mature companies after round D as they will be acquired by bigger firms or they will conduct an IPO (Initial Public Offering) or they will internally grow the business.

We will focus on seed phase to round D start-ups as their valuation is still in high rate of growth and evaluation is challenging to say the least.  These firms are occasionally perceived as dream companies as most of them have no positive cash flows and in some cases it will take years for revenues to realize. On the other hand, dream companies attract investors as Nietzsche once said “Hope in reality is the worst of all evils because it prolongs the torments of man”

Human nature tends to be optimistic in its nature as described extensively in many studies on investor optimism and in part of this book that discusses this extensively. Investors’ optimism is reflected in two main components of valuations: the first is the introduction of overly optimistic activity components, such as significant market growth; Rapid adoption of technology to the market; the perception of a significant market share of the technology in the early years, etc. On the other hand, the expenses are also perceived as optimistic. Research and development expenses are taken in valuations in a relatively minor manner; the expenses are taken for too short a period; Legal expenses and advice frequently required are usually taken in a minor manner, if at all.

The second component that does not receive much attention in assessing dream companies is the discount rate that actually compensates for systemic risk. The compensatory risk of macroeconomic aspects such as regulation, the economic environment in the country in which the company operates, and other aspects over which the Company has no control of.

We will discuss below the ways in which technology companies should be evaluated while exploring firms’ valuation method; at the next part we will dive in into technology valuation.

1. Valuation of companies

R&D company valuations are challenging due to a non-cash valuation with a long time-to-market in most cases. Methods typically used for company valuations, such as asset valuation or multiplier methods, are incompatible with the valuation of R&D companies. In such companies, the current status of business cannot be analyzed by the capital in the balance sheet, and in most cases cannot be compared to similar companies due to their uniqueness, in both technological and financial aspects.

Evaluation of a non-dream firm is generally based evaluating the Company’s operations based on anticipated revenues, fixed and variable expenses in the future and the creation of future cash flows. In addition to the estimation of future discounted, investors and analysts add non-operational assets such as cash and cash equivalents and substracte non-operating liabilities such as loans or bonds as we discribed in privious parts.

Dream companies are first examined by their technology and business model. In other words, the valuation relies primarily on a basic understanding of the technology and how it will affect the area in which it operates and only after that is an examination of the business environment and model. This is in contrast to valuations in the “classic” world in which the market is already familiar and dense enough. In the technological world, the company may re-invent the market in which it operates – what is called distrubtive firm.

Distrubtive firms valuation is based on what can be call Intellectual Property (IP) valuation and how the company is going to make money of it and when (if realized) it will occur. Thus, asserting the IP is based on time and probability of the company’s IP success.

As part of a discounted cash flow (DCF) we describe in previous part, we can summarize technology assessment methods into three main methods within the DCF method:

1. Real Options (Pre-seed firms) – valuation method designated for pre-clinical and early-stage clinical programs/companies where the assessment is binary during the initial phases, and based upon scientific-regulatory assessment only (binomial model with certain adjustments).
2. Pipeline assessment (Seed to round D firms) – valuation method used for programs/companies prior to the market stage. The company’s value is the total discounted cash flow plus unallocated costs and assessment of future technological basis. The assessment of the future technological basis is established based on the company’s ability to “produce” new clinical and pre-clinical projects and their feed rate potential.
3. DCF valuation (Round D+) – this method applies to companies with products that have a positive cash flow from operations.

DCF is the accepted method of evaluating companies with positive cash flows to mature technology companies and therefore we will not discuss them here (this method is described in detail in previous chapters).

Technology companies are de facto holding companies of various technologies, and therefore the valuation of technology companies is in fact an assessment of the company’s technology, that is, the assessment of the company’s intellectual property and its commercial potential.  The company’s valuation is calculated by examining the company as a holding company vis-à-vis existing projects, with Risk-adjusted Net Present Value (rNPV) capitalization to the net present value, including weighting of several scenarios. These primarily include analysis of the company’s income, evaluated in accordance with scientific/technological assessment, based on various sources and estimates relating to the market scope, the degree of projected market success, and regulatory risk.

The weighted average of company revenue is based on the following data:

• Total Market – market potential for the product/product line
• Market Share – the company’s ability to penetrate the market during the forecast period
• Peak Sales – peak sales of the company/product during the forecast period
• Sales curve – in what rate the company will be able to penetrate the market until reaching its peak sales. It is depends on a deep market and technology understanding.
• Annual Cost of Treatment in the life-science case – estimated annual cost per patient, based on updated market studies
• Success Rate – this is the ‘’r’’ in rNPV which we will elaborate below.

The r in rNPV

When evaluating technologies we are actually assuming technology to emerge and become realty by the next coming future. These are for example the chances for success of clinical trials and transition to the next phase in the examined sub-field; success rates for grid-in renewable energy projects; or success rates for new versions of cyber firms to emerge. In the “classic” world of valuation where companies are already selling products for couple of years, there is, in most cases, no question rather the company will continue selling or not. The only question that may raise is what will be the growth rate of revenues and not if there are going to be revenues at all. Thus a probability of the risk of NPV, i.e. rNPV is required. As we will approach market and revenues, probability will become 100%.

In life-science, success rates or attrition rates are commonly known. They are based on numerous clinical trials and regulatory filling that have conducted throughout the years and gathered in academic and/or governmental websites like clinicaltrials.com (a U.S official website where all clinical data should be included) and the FDA official website (FDA.gov). We will describe these success rates in an example of life-science valuation later in this section.

Renewable energy firms have other milestones and probability based on projects’ development in regulatory, infrastructure and financial aspects. Renewable energy firms need first to win governmental tenders in which government are selling the ability to sell the electricity authority future renewable energy or to join an exciting firm already won a tender. Then, a project needs to merge, i.e. infrastructure and financing are required. All these phases, similar to life-science, bare some uncertainty for future cash-flows. We describe below success rates for solar and wind energy projects by phases:

Once we have the basic figures we now need to understand the business model. Renewable energy firms can be divided into two groups: 1) opportunist companies seeking projects around the world taking position in different phases of the project. We will see higher financial leverage in these companies; 2) end to end companies taking the project from initiation to build and operate the project.

However the difference, there is no major variance in evaluation these two types of companies beside of building the WACC model as debt to equity will be different.

In other technology companies it depends if the company is sales orientated seeking to sell its product by itself or it seeks for a strategic partner or distributer. If the company will choose to go alone, rNPV model is straight forward – analyzing sales by quantities and prices. If the company seeks for partner to sell its products, business model is more research and development focus while the company anticipates royalties and milestones. Deal structure in this case is based on market demand for the product – the higher demand is the better deal structure the company will receive. In the life science domain it is based on previous similar deals and the clinical and regulatory phase the company is in. As a company will enter into out-licensing deal earlier it should expect lower royalties and lower milestone payments and the other way around.

1. Valuation of technology

Technology companies as said are viewed as holding companies of technology projects they are develop. Main question arises when we need to evaluate future potential. Unlike non-dream companies we cannot use the dividend model or Gordon’s (1969** check) model as technology has expiring date – for drugs it’s the patent period; for cyber companies is the time a new version will be valid; and for renewable energy company is the time the PV plates or wind turbines will have to stop operating due to end of a governmental tender or due to operational reasons.

Thus, technology valuation is based on first previous evaluation of the company’s projects, as it already uses the core technology so we can assume more similar projects to come in the future. To wit, the holding company may produce more technology projects based on its platform.

A product pipeline is supported by the company’s broad business and technological base. Valuation of a company “technological basis” is in fact a valuation of the company’s “residual value”. This valuation was conducted using the Feed Rate methodology that is common, rather than using the conventional terminal value, normally used by non-tech companies, for the following reasons:

• The terminal value reflects a type of steady state in company sales with a certain fixed growth rate (g) based upon past data. This is not the case for life science companies, where the terminal value is derived from projects in development.
• The terminal value for a given company usually constitutes between 70-80% of its worth. In contrast, the main share of the value of a life science company is attributed to income generated during several years following product launch (for the most part, approximately 6-10 years), after which a certain decline occurs (for example, expiration of a patent, and the emergence of competing products).

The technological platform valuation is based on the average number of new projects that a company can yield annually. Estimating the capitalization value of future projects is based on pre-clinical and clinical development aspects or technology developments, assessment of unallocated costs, and a higher capitalization rate than the one used during the forecast years, due to the uncertainty of the company’s future projects.[1]

Let’s take an example to asset main technology platform valuation points:

• We assume one new project every four years (based on understanding the company’s technology and addressable market) with an average value of $59.1M (equal to the average value of the current pipeline programs).
• Unallocated costs are mainly G&A and sales costs, with a similar share from the project’s value as in the current pipeline programs
• We estimate unexpected costs to be 10% of the average value
• Statutory tax rate of 15% is assumed, which is lower than a federal tax of 35%
• The capitalization rate is higher than the one used in the pipeline valuation, reflecting increased uncertainty
• It is assumed that the “platform” generates projects for n years: in our valuation, and based on the average patent period, n=13 years. We therefore subtract all projects generated after n years from the technological platform value.

The following formula reflects the value of the technology:

Main valuation parameters of the technological platform:

In the following examples, we will take step by step to show how to implement these parameters in real-life analysis of two different types of firms`           activity – evaluation of a life-science round B firm and a similar valuation for renewable energy firm.

Section 2: Introduction to valuations in R&D intensive industries

Chapter 3. Understanding the pharmaceutical industry

The pharmaceutical industry develops, produces, and markets drugs to be used as medications. It is one of the world’s top five industries by revenue and capitalization, with total annual revenue exceeding $700 billion in recent years. The majority of these earnings are attributed to multinational pharmaceutical giants that have been dominating the industry for decades. Over the past twenty years the industry has been undergoing seismic shift due to rapidly developing biotechnological advents. This has created a niche for smaller pharmaceutical firms, generally pursuing the development of a single drug.

The modern pharmaceutical industry came of age with the introduction of regulations demanding that new pharmaceutical products be proven both safe and effective before they are marketed and sold. In the US, such legislation was introduced in 1962 with an amendment to the Food, Drug and Cosmetics Act (DiMasi, 2001). Since the introduction of these requirements to demonstrate pharmacological efficacy, the industry has become a major driver of advances in health technology, and accordingly research and development expenditure has increased significantly.

In the US, new pharmaceutical products must be approved by the Food and Drug Administration (FDA), both for safety and efficacy. This process generally involves submission of an Investigational New Drug (IND) filing with sufficient pre-clinical data to support the commencement of human trials. Following IND approval, three phases of progressively extensive human clinical trials are conducted. Phase I generally studies toxicity, using healthy volunteers; Phase II examines safety and efficacy in patients; and Phase III studies efficacy on a much larger scale, by experimentation among the target patient population. Following successful completion of Phase III, either a New Drug Application (NDA), or a Biologic License Application (BLA) for bio products, is submitted to the FDA. The FDA reviews the submission and if the product is perceived as having a positive risk-benefit assessment, approval to market the product in the US is granted (Walker et al., 2011).

The required documentation for an NDA consists of the drug development history during pre-clinical and clinical phases, its ingredients and their behavior in the human body, as well as; manufacturing, processing, and packaging procedures. BLAs for biological products are approved for marketing under the provisions of the Public Health Service (PHS) Act, which requires the manufacturing firm to possess an interstate commerce license for the product. The required documentation of a BLA contains specific information on the manufacturing processes, chemistry, pharmacology, and medical effects of the product.

Due to the rigorous drug development process, multiple and increasingly larger investment rounds are required. Many drug development companies choose to raise funding by issuing securities and registering them on stock exchanges. As a result, by the end of 2012, more than 500 healthcare companies have listed on US stock markets. Frequently, the stock prices of these firms are highly volatile, manifesting the rapid information updates regarding the clinical progress and regulatory issues.

During the protracted journey towards FDA approval, the company usually disseminates numerous press releases; most of them hit the market without any prior notice.

5.1 The drug development process

Clinical studies are always conducted under the guidance of a regulatory agency. While initial clinical studies can be performed under domestic regulation (such as the Public Health Service (PHS)), drug companies seeking to sell a drug in the United States or the EU must first test it according to the guidelines of the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) respectively. In this section we focus on the FDA’s regulatory procedure.

In general, there are three phases of clinical development, and a drug must meet success criteria at each phase before moving on to the next:

Phase 1’s main goals are to assess safety and tolerability, and explore how the drug behaves in the body. This phase addresses questions such as; how long does the drug stay in the body? And how much of the drug reaches its target? This phase is usually conducted in healthy volunteers.

Phase 2’s main goal is to evaluate whether the drug is effective in achieving its intended therapeutic effect upon its patients, to further explore its safety, and to determine the ideal dosage.

Phase 3 comprises large studies involving 500 to 5,000 or more patients, depending on the disease and the study design. Very large trials are often needed to determine whether a drug can prevent negative health outcomes. Often the goal is to compare the effectiveness, safety, and tolerability of the test drug with another drug or a placebo.

The size, duration, costs and number of trials of each clinical phase may vary according to the drug, the disease and the regulatory pathway. If the drug candidate shows clear benefits and acceptable risks in phase 3, the company can file an NDA, requesting regulatory approval to market the drug. Regulators review data from all studies and decide whether the drug’s benefits outweigh any risks it may have.

The range of costs and duration of drug development are depicted below:

Costs and duration of drug development

The process of filing a request for initiating conducting clinical trials in preparation for marketing approval in the US (under FDA guidance) is termed an “Investigational New Drug (IND) application”. This application should include a full pre-clinical package; the drug’s efficacy, toxicology, and ADME (absorption, distribution, metabolism, and excretion). In addition, as described above Chemistry and Manufacturing Controls (CMC) information, regarding the quality/purity of materials used the drug’s production process and the analytical testing procedures it has gone through to ensure its quality, also need to be submitted alongside.

During the IND application process the drug developer receives feedback from the FDA regarding the regulatory procedure the drug candidate will go through towards marketing approval, including which regulatory pathway its approval will take. It is important to note that a company that has not conducted clinical studies under an IND is likely to be asked by the FDA to perform additional studies of the same phase under the IND application.

Preparing materials for an IND application is exorbitant and laborious. Nevertheless, it is necessary for proper advancement of the product’s clinical development. Moreover, a drug candidate that had completed the IND application process and gone through clinical studies under that IND would be a more attractive target for a licensing deal compared to a drug that hadn’t gone through that process.

Regulatory pathways for drug approval

For decades, the regulation and control of new drugs in the United States has been based on the New Drug Application (NDA). Since 1938, every new drug has been subject to an approved NDA prior to commercialization anywhere in the US. The NDA application is the vehicle through which drug sponsors formally propose that the FDA approve a new pharmaceutical product for sale and marketing in the U.S.  The data gathered during animal-based studies and human clinical trials of an Investigational New Drug (IND) become part of the NDA.

The goals of the NDA are to provide enough information to permit FDA reviewers to reach the following key decisions:

The documentation required in an NDA is supposed to tell the drug’s whole story, including detailed recounts of clinical tests, what the ingredients of the drug are, the results of animal-based studies, how the drug behaves in the body, and how it is manufactured, processed and packaged.

The FDA outlines three different regulatory pathways for drug approval. Below these are segmented according the complexity of the New Drug Application (NDA).

The different new drug application (NDA) pathways under FDA guidance

505(b) (1) regulatory path

A clinical submission filed under FDA Section 505(b) (1) needs to clinically demonstrate meaningful treatment benefits with statistically significant safety and efficacy objectives and endpoints. It furthermore has to comprise a new chemical entity targeting a new indication. The new investigational drug will be administered to the patient in a new formulation, applying a new dosage form and strength, with all the above being collectively patented. NDA approval under section 505(b) (1) is granted by the FDA only after extensive Phase 1, 2, and 3 clinical development programs. When all three clinical phases are complete, the host company and/or manufacturer, submits an NDA to the FDA encompassing comprehensive results from all studies, be they; nonclinical, preclinical, clinical and/or pharmacokinetic.

NMEs are specific cases within the 505(b) (1) regulatory path and by definition can’t be a part of any other regulatory path as they are “new”. On the contrary, not all 505(b) (1) regulatory pathway drugs are NMEs. In some cases, the FDA can ask the host company to conduct a full clinical process, following major changes in dosages or chemical structure.

NME (New Molecular Entities) – the innovation edge

Drugs are classified as New Molecular Entities (“NMEs”) during NDA 505(b) (1) for FDA review purposes. Many of these products contain active moieties that have not been previously approved by the FDA, either as a single ingredient drug or as part of a combination product. These products frequently provide important new therapies for patients. Some drugs are characterized as NMEs for purely administrative purposes because they contain active moieties that are closely related to those found in products that have previously been approved by the FDA. Furthermore, the FDA classifies biological products submitted in an application under section 351(a) of the Public Health Service Act as NMEs for the purposes of FDA review, regardless of whether the Agency has previously approved a related active moiety in a different product.[2]

NME designation indicates that a drug in development is not a version or derivative of an existing and previously investigated trialed and approved substance. Being labeled as entirely ‘new’ or first-in-class molecule dictates that certain types of clinical trials must be run, and that particular attention must be paid to proving a drug’s safety.

Drug efficacy is often demonstrated through a comparison with existing drugs and treatments. However, an NME being explored as a treatment for a previously untreated condition means there are no existing treatments, or even similar drug products, against which efficacy can be measured.

This situation requires that other measures of efficacy be located and measured; such as quality of life scores and deep, detailed attention to direct physiological impacts of the drug’s mechanism of action and effect upon the symptoms and physiological attributes of the disease or disorder that is being targeted.

The NME novelty carrys with it a promise of economical potential as the molecule can treat unmet patient needs in some cases, and in other circumstances can ignite further drug development.

NME`s within the FDA approval track

In 2012, the FDA’s Center for Drug Evaluation and Research (CDER) approved 39 new molecular entities (NMEs), representing 1% of all the FDA`s approvals for that year. This includes applications for both New Drug Applications (NDAs) and Biologics License Applications (BLAs). This reflects the highest total for 2003 through 2011 where CDER has averaged about 24 NME approvals per year. The application rate averages about 32 applications for NMEs per year. In 2011, CDER approved 30 new molecular entities (NMEs).

More than half (20 of 39; or 51%) of the NMEs approved in 2012 were identified by the FDA as ‘First-in-Class’, meaning that those drugs use a new and unique mechanism of action for treating a medical condition. ‘First-in-Class’ is one indicator of the innovative nature of a drug and a 51% First-in-Class approval rate suggests that the group of 2012 NMEs is a field of highly innovative new products. Additionally, 13 of the 39 NMEs in 2012 (or 33%) were approved to treat rare or “orphan” diseases.

505(b) (2) regulatory path

The 505(b) (2) is a type of abbreviated NDA that is applicable for development of a drug that is based on the modification of an existing, approved drug. It is a drug development program with a diminished burn-rate and faster time to market. The development program is abbreviated because existing information on safety and efficacy exists in the public domain and can be used for the 505(b) (2) NDA approval. Thus, the 505(b)(2) usually does not involve the typical wide ranging clinical studies associated with a 505(b)(1) NDA, instead they usually rely upon relatively short and inexpensive bridging clinical studies to relate the safety and efficacy of the new 505(b)(2) product to the related NDA product. However, drugs that receive a marketing approval through this pathway, are granted a shorter market exclusivity period by the regulatory agency (3 years, compared to the 5 years in the 505(b) (1) pathway).

Other types of applications

Regulatory agencies, such as the FDA (US) and EMA (EU), are advancing the evaluation and development of products that demonstrate treatment of rare diseases or conditions. A rare (orphan) disease is defined as one that affects 0.05-0.1% of the population (depending on each agency’s guidelines).

Incentives for orphan drug development provided by the FDA and EU Commission include special regulatory protocols, extended market exclusivity (7 years in the US, 10 years in the EU), reduced fees for regulatory activities, centralized application (in the EU only), tax credits and an accelerated approval process.

An Abbreviated New Drug Application (ANDA) contains data which when submitted to the FDA’s Center for Drug Evaluation and Research, Office of Generic Drugs, provides for the review and ultimate approval of a generic drug product. Once approved, an applicant may manufacture and market the generic drug product to provide a safe, effective, low cost alternative to the public. A generic drug product is one that is comparable to a visionary drug product in dosage form, strength, route of administration, quality, performance characteristics and intended use.

Generic drug applications are termed “abbreviated” because they are generally not required to undergo preclinical (animal) and clinical (human) trials to establish safety and effectiveness.  Instead, generic applicants must scientifically demonstrate that their product is bioequivalent (i.e., performs in the same manner as the original drug).

Over-the-counter (nonprescription) drugs are defined as drugs that are safe and effective for use by the general public without seeking treatment by a health professional.

Milestone events under FDA regulatory paths

Throughout the regulatory process, once a company has filed an NDA, there are two milestone events, namely advisory committee (AdC) and the FDA final announcement of marketing approval (or non-approval). Those events, the “holy grail” of the drug development process, are well-known in advanced, published on the FDA website, as obligated by Federal laws.

The Federal Food, Drug, and Cosmetic Act of 1938 was enacted after a legally marketed toxic elixir killed 107 people, including many children. The FD&C Act completely overhauled the public health system. Among other provisions, the law authorized the FDA to demand evidence of safety for new drugs, issue standards for food, and conduct factory inspections. Nowadays, according to the FDA, it regulates $1 trillion worth of products a year. It ensures the safety of all food except for meat, poultry and some egg products; ensures the safety and effectiveness of all drugs, biological products (including blood, vaccines and tissues for transplantation), medical devices, animal drugs and feed, and makes sure that cosmetics, medical and consumer products which emit radiation do no harm.

The FDA`s AdCs play an essential role in their activities to protect and promote public health through the regulation of human and animal drugs, biological products, medical devices, foods, and tobacco products. It provides independent expert advice and recommendations to the Agency on scientific, technical, and policy matters related to FDA-regulated products. Advisory committees enhance the FDA’s ability to protect and promote public health by ensuring that the FDA has access to such advice through the public hearing process as provided in existing laws and regulations.

Although AdCs provide recommendations to the FDA, the organization makes the final decisions on any matters considered by an advisory committee. The FDA encourages transparency in this formal event, and throughout the decision-making processes. Every AdC meeting includes an open public hearing (OPH) session, during which interested persons may present relevant information, either orally or in writing. Furthermore, the time and location of the meeting and the OPH session is published in the Federal Register (21 CFR) at least 15 days before a meeting.

Understanding the pharmacuticals industry as described above may be also a door to better understand other technology domains as smart mobility.

Ride-sharing Platforms and Pharmaceutical Companies.

There has recently been a lot of attention surrounding the long-anticipated IPOs of ride-sharing companies, Uber and Lyft in the US.

Analysts have cautioned investor excitement, emphasising that these companies are not only yet to turn a profit, but also continue to post heavy losses. Many believe that investment in the company can only be justified, particularly with respect to Uber, as the “Amazon of transportation”. In other words, by hoping for future expansion of other businesses such as micro-mobility (e-scooters and e-bikes), food delivery and so on, which are already profitable for the Company. Others say that shareholder pressure will see these Companies take more from both their drivers and/or their riders.

There is another way to view these companies that is rather unconventional – as R&D intensive companies, i.e. a company without a product ready for market. This has become a well-known operating model particularly in early-stage technology companies (or ‘start-ups’) and most especially in life-sciences.

Ride-sharing companies spend billions on branding and marketing to consolidate a loyal customer base, to attract R&D partnerships with OEMs, and invest in their own R&D. This is well justified as it brings closer an era of autonomous and electrified ride-sharing, in which these Companies won’t need to pay drivers the 75% commission they currently receive. Revenues today comprise only 25% of ‘Gross Bookings’, but with autonomous and electrified fleets – they will comprise 100%.

Life science companies, especially pharma and biotech companies, burn millions of dollars from day one as they seek to prove the safety and efficacy of their treatments. Early-stage life-science companies have a proportionately higher burn-rate as regulation prevents them from turning a profit in the short term, without FDA approval. Larger pharmaceutical companies however, might incur a loss for several years as they develop a new innovative drug, yet partially offset these expenses by continuing to sell the current gold standard, regulatory approved treatment. Ride-sharing companies more closely mirror these larger companies by using the current automotive standard (human-driven vehicles) to bring in short-term revenues, with long-term profitability reliant upon autonomous and electrified fleets.

The ability to bring in 100% instead of 25% of gross bookings is dependent only on vehicle autonomy. So why is electrification so important? Well, this extra revenue doesn’t come for free – nothing does! Ride sharing companies, in addition to existing corporate costs, will need to fund the costs that are currently covered by drivers; fuel, maintenance, vehicles, accessories, and so on.

Two important points here.

• In terms of CAPEX, if these Companies choose to purchase their fleets, the vehicles will appear as fixed assets on their balance sheet. This will boost non-current assets, with current-assets already strong, particularly levels of cash on-hand.
• On the OPEX side of the equation, drivers have reported the most expensive operating expense to be fuel, so electrification, provided enough infrastructure continues to be provided, and electricity prices remain stable, will provide major cost savings.

A hatchback (the most common model among uber drivers) costs $540 to charge per year, assuming annual trips of 15,000 miles (i.e. we are looking at driver’s in very dense city centres; Manhattan, City of London, Tel Aviv) fuelling a new, fuel-efficient Hyundai i30 (a popular hatchback ride-sharing vehicle) costs more than eight times that amount.

To get a sense of this impact, let’s assume that between 2016-18 both companies offered ride-sharing services in their own autonomous and electrified fleets, i.e. revenue = gross bookings. We account for three scenarios;

1. Costs remaining stable – Essentially impossible
2. Costs doubling – If the companies purchased their fleets, though depreciation would be high this would be partially offset by savings from replacing fuel with electricity. However, the companies might have to provide for their own infrastructure, which would also depreciate. The scale of operation particularly in cities with high labour costs; R&D, Cyber and so on would also cause steep cost increases.
3. Costs tripling – A very highball estimate

The results are staggering, for the most realistic of these three scenarios (costs double) both companies are profitable for every reporting year (aside from Lyft in 2016 which would have lost $167M). If costs triple, our highball estimate, Uber still manages to post an impressive profit of $6.9B in 2018.

Figure 1: When Gross Bookings become Revenue. Operating Profit/Loss (USD Millions)

Such potential revenue increases, and the possibility for other savings (driver welfare, driver commissions, driver insurance – the list goes on) has even raised the possibility of erasing cost to the consumer entirely. Future fleets of shared, autonomous, and electrified vehicles can monetize off advertising the way other software companies do. Waymo, a subsidiary of Google has by far the most miles driven of any autonomous vehicle company or car manufacturer and is already offering rides in autonomous vehicles to commuters in Phoenix (through Lyft). As the world’s number-one advertiser, Google could seamlessly integrate its clients into Waymo’s ride-sharing app, and through screens in the vehicle’s interior.

So, what’s the bottom line here? These companies will become profitable. Autonomous vehicles are creeping up on us. Uber’s autonomous fleet has driven 27,000 miles itself, Waymo has driven 1.3 million miles and has partnered with Lyft, GM has partnered with both Uber and Lyft and has driven 450,000 miles, Volkswagen invested $300M in Gett back in 2016 – the list goes on, this is no longer science fiction – it is science fact!

The investment opportunity – a comparison with the life sciences

The hype surrounding the listings of ride-sharing companies led to an inflated IPO price that has since dropped heavily for both companies and historical data shows a similar trend in life-sciences.

Both industries are heavily regulated for safety and efficacy, in the pharma case the safety of the drug, and efficacy of treatment, and in the automotive case the safety of the vehicle and efficacy in preventing road accidents. The regulation’s stringency in each is due to its outcomes being life-threatening. This influences investor behaviour with respect to the risk profile of both industries.

There is also a striking similarity in milestone analysis. Life-science companies will IPO in the early stages of the FDA approval process, which comprises several phases of clinical trials; Pre-clinical, Phase I, Phase II, Phase III and Phase IV. Investors in the life-science space often execute trades around the decisions of the FDA in approving a treatment passing each of the clinical milestones.

Automotive manufacturers aspire to conquer the SAE’s five levels of vehicle autonomy; Driver Assistance, Partial Automation, Conditional Automation, High Automation and Full Automation. However, there is no suggestion that milestone-based trades occur in high volume in the ride-sharing space. Lyft stock was not responsive to a major announcement early this month that Waymo was rolling out level-4 autonomous robo-taxis on the Lyft app, in the pharmaceutical industry the share price would skyrocket around a comparative announcement.

In the case of pharma companies, the success rates of getting through the FDA process are low and unpredictable not only due to the internal scientific inquiry, but also due to external factors such as competition, funding constraints, and regulatory shocks. They are also subject to post FDA approval risks like the reimbursement policies of insurance companies. The predictability of Autonomous vehicle milestones are even less clear-cut and therefore the relationship with the market is too.

Some words of caution

A major caveat however is that the FDA process and its equivalent in other geographies is designed to reward successful pharma and biotech companies with economic monopoly in the initial years following regulatory approval. This generally occurs until the expiry of the original patent (usually 10-yrs) but can be extended under certain circumstances such as that of ‘orphan drugs’ treating rare conditions. In the mobility case, it is a highly competitive race between a few to the finish line. With nearly every major automotive manufacturer in the running the autonomous automobile market looks set to be as oligopolistic and it is today with human drivers. Another important caution is that no ride-sharing company has been listed for more than a single financial year. It’s very early days and increases in demand for ride-sharing stocks in accordance with successful milestone-based progress in autonomous vehicle testing, might be something the markets will soon exhibit.

Lessons for valuations of disruptive technologies

To conclude, when dealing with emerging technology in new industries analysts will most certainly suffer from information and precedent scarcity. There is certainly benefit in looking at the elements of value and the timing of their actualisation as revenues and conceiving of new models based off totally divergent industries that bare similar characteristics in this respect. The lead-time of new products in cybersecurity or enterprise software is long in comparison with manufacturing, but short in comparison to life sciences. When faced with new challenge of valuing autonomous vehicle companies and one might naturally expect answers to be found in industries with operational and product-based similarities like manufacturing or software as these are components which come together to form the new product. However, as demonstrated above sometimes the valuation precedents or insights to help you build a new model are hidden – they don’t lie in the obvious place. Analysts tackling new technologies, companies, and industries will therefore benefit from having a more holistic knowledge of many different industries and the financial valuation nuances in each. Whilst no analyst can be a specialist in every industry understanding the foundations of large well researched and precedent rich industries will increase the chances of finding helpful building blocks for conducting a corporate valuation of a information scarce candidate.

Ch. 4 a Glance to Cyber-security Market: Network Security

Cyber-security is a vast domain. We choose to focus on the main stream within this industry in order to supply a basic understanding of cyber-security over the network we all use with our phones or computers.

Developments in communication and associated technologies have undergone a meaningful change. The plethora of connected devices, connectivity protocols and applications enable unprecedented access to and transfer of data and information. As the dependence of consumers and enterprises on networks for myriad requirements grows, so does their vulnerability. Attacks can cost millions of dollars, impact competitiveness and damage reputation of companies which increases customer churn. The high complexity of systems and networks enhance vulnerabilities making the task of securing them even more challenging.

Network security utilizes software and hardware technologies to maintain integrity, confidentiality and accessibility of networks and data.  Effective network security can thwart unauthorized access and stop a variety of threats from entering the network via policies and controls implemented across multiple layers at the edge and in the network. Network security uses different practices such as active and passive deployment of software that can track, and stop malicious activities; preventive deployment to identify potential threats and security glitches; and ensures that users are aware of and following security protocols.

Network security providers are capable of a comprehensive assessment of network architecture and evaluation of the security of Internet and Intranet connections. A customized security solution based on users’ systems comprising different components such as firewalls can be provided. Additionally, monitoring and end-to-end visibility enable better network security management. After a thorough vulnerability assessment, network security is deployed along with threat intelligence, endpoint security, application security, and other cybersecurity services.

The primary areas of application of network security are detailed in the graphic below:

With the implementation of the Network and Information Security Directive (NISD) and the General Data Protection Regulation (GDPR) in the EU in 2018, operators must ensure that their network and information systems meet minimum standards of cyber security. Multiple incidents and vulnerabilities reported in recent times targeting communication service providers mandate proactive response plans and tools to deal with legal, operational, technical, reputational and regulatory risks. CSPs with their core infrastructure and the large volumes of personal data they hold on subscribers, become target for malicious incidents. With Allot’s solution, CSPs can both protect their own network infrastructure and offer value added Security as a Service (SECaaS).  The areas where network security may be provided as a service to subscribers are covered below and are compared in the “Competition” section of the report.

Trends Impacting Network Security Market

1. Zero-trust approach to network security—the zero-trust approach has moved beyond being a buzzword and with BYOD, cloud computing, and remote workers, its adoption will soon be mandatory as a network security best practice. Insider threats are occurring in alarming proportions and devising methods to mitigate these is the way forward. This mandates visibility and mapping of secure access to data and resources based on user and location. It helps to reduce pathways for attackers and malware. It also requires inspection and logging all traffic, implementing security rules based on business policies and using multiple authentication methods to counter attacks.
2. Enterprise mobility changes the requirements—Emergence of the BYOD trend is directly related to an increase in enterprise mobility as companies adjust to employees’ preferences for smartphones, tablets, and portable computers at work. The network security framework and solutions undergo changes to meet BYOD enabled workplaces. Network security solutions must be flexible to adapt to different operating systems, hardware and software.
3. Advanced technologies in network security— AI and ML-enabled network security systems enhance existing defense capabilities and over time ‘learn’ to identify unusual patterns and malicious activities. This helps to detect and stop known threats. The real value is however when encrypted web traffic can be monitored for unseen variations of known threats or related new threats or new malware threats. Automatic alerts regarding unusual patterns to security teams increase the effectiveness of the system by dealing with skills and resource gaps.

Factors Driving Adoption of Network Security

The exponential increase in connected devices and consequently the increase in data and information that networks have access to, mandate the presence of comprehensive security.

Factors Constraining Adoption of Network Security

Lack of standardization and fragmentation creates confusion among users. While they look for integrated products and services, network providers need to find partners in the ecosystem with similar goals and approaches when it comes to importance of security.

Challenges / Insights

Different approaches to security—Network complexity increases manifold as a host of different industry participants and third parties come together to help a network function. Importance of network security will be at different levels of priority and not all third party providers will invest equally. Their approach may leave some weak spots in network security.

Breaches go undetected—In spite of implementing network security, it is important to constantly monitor networks since breaches can go undetected for months. To prevent this, efforts to monitor across multiple layers are made to enable comprehensive monitoring and control.

Development of Comprehensive Ecosystem—Over the last few years network security has moved beyond piece-meal implementation to creating end-to-end solutions. As ISPs offer this as a value added service to customers, the solution becomes a critical entity in ensuring protection not just for end users but for ISPs themselves. To ensure this, multiple innovative companies – large firms, start-ups and technology enablers are working together to enhance and create effective solutions. Increasingly platforms that can integrate different components from different providers are becoming go-to solutions.

Use cases

Below are several use cases where Network Security is used:

• For end-to-end network traffic inspection: Network security has moved beyond perimeter security to include communication in the cloud, and network communications from remote locations to software as a service (SaaS) applications.
• Work across encrypted/decrypted solutions: While most data is encrypted, the network security can detect suspicious traffic without the need to decrypt each time.
• Secure access with network security solutions ensure only trusted users such as end-user devices, APIs, IoT, micro-services, and containers, gain access. It prevents gaps in visibility. Better visibility enhances threat detection, highly secure access, and software-defined segmentation.
• Providing protection from ransomware and to prevent entry from the DNS layer to email to the endpoint.

Future Trends

Increase in use of mobile devices to launch attacks: Mobile phones and connected devices are likely to be used to breach network security given their propensity to be more vulnerable. As end users use the same devices for business and personal use, end point security becomes critical. According to RSA’s 2019 Current State of Cybercrime whitepaper, ‘70% of fraudulent transactions originated in the mobile channel in 2018’. As the next generation of communication advances with 5G, it also means an increase in the attack surface area for ISPs. The complex and faster networks can expect more malware, security breaches and DDoS attacks.

Automation of security systems: Automation creates an added layer of security that is not dependent on human action to secure networks. There is a lack of skilled professionals in the industry, and to enhance their capabilities and utilization, automation can be a critical tool. Most customers lack the requisite expertise and rely on third party providers, another reason for the trend to gain popularity. The growing trend of adoption of AI and ML to power solutions will also contribute. Benefits of these technologies include enabling better response rates, pre-empting threat detection, and insights on effective mechanisms to reduce threats.

Unification and standardization of security orchestration: Network security providers are increasingly looking at ensuring integrated solutions for comprehensive solutions. Haphazard expansion of digital ecosystems can leave systems vulnerable to attacks. Regulations such as GDPR will work towards curbing malpractices and put greater focus on compliance. Since hackers can utilize multiple entry points such as emails, public clouds, etc to enter the system, the need for end-to-end systems to prevent networks with established standards will continue to grow. This should also feed into all network security controls (i.e. physical, virtual, cloud-based) reporting into a common control panel for various activities such as configuration, policy, and change management.

Chapter 7. The use of multiples – The First Chicago Venture Method. What is it and when is it used?

The use of multiples – The First Chicago Venture Method. What is it and when is it used?

Multiples can be very helpful, however in most cases they can be used only as a benchmark. In Research and development companies multiples can be used for revenues multiples as similar companies may sell in similar ways.

Research and development multiple is more commonly use in view of mature companies vis-à-vis early stage companies. For example, Research and development expenses are 100 while a mature company market value is 1,000 thus the Research and development multiple will be 10. If a young company Research and development expenses are 20 and we expect it will reach sales in 3 years as the mature company we took as a benchmark, the multiple will be 10/(1+r)^3 where r is the capitalization rate. Assuming it is 10%, multiple will be around 7.5, i.e. the young company market value will be 7.5 multiple by 20 (company’s expenses) – 150. Thus, we are discounting the multiple. Some call this method the First Chicago Venture Method or FCVM to imply as a quick and dirty benchmark for young technology companies.

Different multiple that can be use is employees multiple. The basic idea is the Research and Development Company will hire the optimal number of employees and mainly high skill Research and development employees. Thus taking market value of publically traded technology companies and number of employees can also serves as some benchmark. Furthermore, number of users or any other operational factors. The main idea here is that we can discount the multiple of mature companies. The main challenge will be to find the specific similar companies and for that deep knowledge of the technology and the market is needed.

Below is an example:

A cyber-security young company is primarily targets the following markets: Managed File Transfer (MFT), Cloud Access Security Broker (CASB), and Software-Defined Perimeter (SDP). Below is a general outlook on the markets:

The following publicly-traded companies are operating in the specific company’s markets:

• Axway Software SA (Euronext: AXW.PA) – a France-based company engaged in software development. AMPLIFY, its core product, is a cloud-enabled data integration and engagement platform, which enables businesses to manage their customer experience networks.

• Attunity (NASDAQ: ATTU) – provides Big Data management software solutions that enable access, management, sharing and distribution of data across heterogeneous enterprise platforms, organizations and the cloud. The Company’s software solutions include: data replication and distribution (Attunity Replicate, Change Data Capture (CDC), and Attunity Gold Client Solutions), test data management (Attunity Gold Client Solutions), data connectivity (Attunity Connect), enterprise file replication (Attunity RepliWeb), managed-file-transfer (Attunity MFT), data warehouse automation (Attunity Compose), data usage analytics (Attunity Visibility) and cloud data delivery (AttunityCloudBeam).

• Globalscape (NYSE: GSB) – provides secure information exchange capabilities for enterprises and consumers through the development and distribution of software, delivery of managed and hosted solutions, and provisioning of associated services. The Company’s primary product is Enhance File Transfer (EFT). Its software products and services include Managed File Transfer Solutions (MFT), Secure Content Mobility Solutions, Wide Area File Services (WAFS), Managed E-Mail Attachment Solution, Consumer-Based File Transfer Solution, and professional services. Its solution portfolio facilitates transmission of critical information, such as financial data, medical records, customer files, vendor files, personnel files, transaction activity and other similar documents.

• CyberArk Software Ltd. (NASDAQ: CYBR) – provides information technology (IT) security solutions that protect organizations from cyber-attacks. The Company’s products include Privileged Account Security Solution and Sensitive Information Management Solution. Its Privileged Account Security Solution enables its customers to secure, manage and monitor privileged account access and activities. The Company’s Privileged Account Security Solution consists of its Enterprise Password Vault, SSH Key Manager, Privileged Session Manager, Privileged Threat Analytics, Application Identity Manager, Viewfinity and On-Demand Privileges Manager.

(Data as of December 31, 2018)

The comparison above provides a glance into the company`s operational activity.  Our company “revenues per employee” were $23K as of the end of 2016, whereas the average for the four above-mentioned companies is $189K.  However, as our company is a young firm, its R&D expenses per employee ($32K), which represent the company’s investment in future operations, is higher than the $24K average of these four publicly-traded companies. In this case we can multiple $24k average research and development expenses with our company expenses and receive it market value, i.e. about $25M.

Chapter 8. Valuation through the use of real options. What is it and when is it used?

Real options valuation is based on options pricing and the well-known Black and Shultz option model (1973).[3]The model is simulating several scenarios for the company’s growth and market. That is unlike DCF where the market does not change, i.e. once we have fixed our estimate on peak sales correspond to the market’s growth. Whatever happens, there is about the same probability that the actual outcome lies above or below the estimated number. On average, the sales equal to what we have predicted. Thus, DCF assume one scenario, i.e. the average. This can lead to over-reliance on this scenario that is still a vague estimate. Also, the reduction of the future to just one scenario avoids considering alternatives in case the estimate turns out to be wrong or must be adjusted due to new information. This would correspond to a statistic outcome that should be considered.

Taking few scenarios into consideration is common acts with analysts in which one can take optimistic, realistic and pessimistic scenarios, however market size and company’s growth are in most case do not change. DCF values the project as if the management takes a one-time go or no-go decision. It would be reasonable to assume that the company alters its plan if one critical measure deteriorates or maybe improves way above expectations. In other words, DCF cannot capture at the stage of valuation all flexible scenarios.

The Real Option Valuation (ROV) takes into account that some decisions in a project’s or in a company’s life can or even must occur at a latter stage depending on future market conditions; therefore can be fundamentally different from current market conditions. The novelty of ROV compared to DCF is that some future decisions about the ongoing of the project or company are conditioned on the respective market condition. DCF assume that the course of the project is predefined, no matter what happens.

In order to correctly model the decisions, it is necessary to model the conditions, or parameters, they depend on. For this ROV theory makes use of the extensive research in the field of financial options that deal with the same cases. When dealing with early stage firms we must model the different ways to react to a change market environment. These different reaction types define the different embedded real options in a project or in a company. The existing literature provides six categories of real options based upon the types of managerial flexibility:

Option to defer; Option to expand; Option to abandon; Option to switch; Option to stage investments; Option to grow. [4] Most of these options are self-explanatory. We will focus on the option to stage investments as this option is in used with technological firms. Some projects require a staged investment. The firm resolves in every subsequent stage further uncertainties. Based on the parameters, the project is revalued and consequently continued or abandoned after each phase. These staged investments are modeled as compound options. After each period the company has the option to continue or not. Continuing corresponds to the acquisition of a new option. In cybersecurity companies, a company can develop one version and based on a successful version it can continue or stop the program. In life-science, a company may out-license its IP based on its clinical and/or regulatory phases.

Most common way to approach ROV is the use of trees. Trees are a simplistic model of future market movements and are used to value financial options. Binomial trees subdivide the time to market in small time steps and assume that in each time step the market or the peak sales can go both up or down, each scenario with a certain probability. The option value is obtained by calculating the tree back from final leaves to the roots.

Lets take ‘early stage’ company as an example. ‘Early stage’ is an biotechnology firm, ‘classic’ in its business model focusing on one product or one treatment it is seeks to develop and sell. Its business strategy involves in-licensing antibodies, typically from academic institutions, and developing antibody versions through clinical proof-of-concept studies. The company aims to out-license these technologies to big pharmaceutical/biotechnology companies for further clinical development and commercialization of the products. The market the company is operating in is hematologic malignancy within the Oncology therapeutic area.

We need first to understand the addressable market. According to the American Cancer Society (ACS), more than 140,000 people were diagnosed with a hematologic malignancy in 2011 in the US, and an estimated 400,000 people are living with, or in remission from leukemia and myeloma. The US numbers constitute around 50% of hematologic malignancy patients in the 7 major markets. The 2011 leukemia and multiple myeloma therapeutics market was valued at over $8 billion and is expected to reach ~$15 billion towards the end of the decade^[5],[6].

We now turn to understand the competitive analysis, focusing on future treatments that will reach market upon our company’s product will emerge.

Over the last decades we have seen a growing understanding of the subtypes for each blood cancer, and the differences in therapies required for each subtype. In the past decade, new drugs, which are often combined with chemotherapy or radiation therapy, have significantly improved blood cancer cure and remission rates. Newer classes of drugs include: tyrosine kinase inhibitors, immunomodulators, monoclonal antibodies and antibody-drug conjugates. More than 50 drugs are used to treat blood cancers, the major of which are presented below.

In addition to the above mentioned therapies, stem cell transplantation is used for the treatment of patients with certain blood cancers, in order to restore the function of the bone marrow. New stem cell technologies are being developed to address the needs of approximately 70% of patients who need a stem cell transplant, but do not have a suitable donor.

* – Sales figure represents income from all approved therapeutic indications.

** – Philadelphia chromosome-positive acute lymphoblastic leukemia

^# – Hodgkin lymphoma

^## – Systemic anaplastic large cell lymphoma

Although many hematological malignancies cases are managed effectively with current standard of care, disease persistence remains a problem as the disease progresses quickly on cessation of treatment. Therapies directed at defined subsets of patients with high unmet needs, such as elderly patients and patients with certain genetic characteristics, are still required. Furthermore, novel therapies that target the leukemia stem cells population while sparing the normal blood-forming stem cells in the bone marrow are needed.

We now turn to understand the product itself and its clinical, regulatory and financial pro’s and con’s. Lets assume that this treatment, should it reach the market, will be targeted at EphA3-positive cancer patients (the name of the anti-body). We also assume, based on clinical data that EphA3 expression is elevated in about 50% of blood cancer patients.

We now turn to valuation as we have market, competition and specific data of the product. The company is currently assessing the antibody’s efficacy in several hematological malignancies in a phase 1 study. Therefore, we cannot specifically assess the size and competitive landscape of our company target market within the hematological malignancies area. Thus, we used ROV (Real Options Valuation) methodology for analyzing the value. Main valuation parameters are:

• Clinical/regulatory progress: The ongoing phase 1 will end by late 2019, followed by a phase 2 study that is scheduled to end in late 2021. We assume submission in 2025 and launch in 2026, based on company`s assumptions and our estimations on regulatory progress.
• Target market: As explained above, we currently cannot assess which specific cancer indication will be chosen for further clinical development. Therefore, we cannot specifically evaluate the relevant competitive landscape and exact addressable market for this drug candidate. For that reason, in order to valuate this program, we used the combined leukemia and myeloma markets as the target market, and presumed very low market penetration and peak sales values.
• R&D costs: R&D costs are based on common R&D costs for early stages.
• Volatility: This parameter is based upon clinical development attrition rates within the blood cancer therapeutics area. In the Black-Scholes (B&S) model volatility is based on historical stock price volatility. If no historical data can be extract, we can take similar companies data.
• Capitalization rate: the product is in early clinical development stage, which relates with higher rate of market uncertainty as mentioned above. We based our risk adjusted analysis with higher capitalization rate (+5%) compared to the company’s other programs.
• Patent period: Based on the company’s data with no additional extension.
• Out-licensing agreement: We estimated future out-licensing following completion of phase 2 studies, based on similar deal structures as follow: in the years 2023 – 2025 $40M every year and upon success $320M in 2026.

This ROV method is designated for pre-clinical and early-stage clinical programs/companies where the assessment is binary during the initial stages, and based upon scientific-regulatory assessment only (binomial model of B&S with certain adjustments).

One more reason to use ROV is behavioral. Using multiples method is not possible as time-to-market is too far (in most cases its 10-15 years depend on regulatory path and therapeutic area). Using rNPV in most cases can lead to over estimation of company’s value as numerous paramets should be taking into account. ROV is in some way a valuation with minimum freedom degrees, i.e. we evaluate the company with basic conservative assumptions on future market and time-to-market while basing our main assumptions on several elements as we describe below. Thus, our optimism as human beings is been diminish in a way. If we are aware of this, early stage valuation will be, in most cases, more conservative and will reflect all risks on one hand and all oppurtunities on the other hand.

Main valuation parameters

The binomial tree is based on the parameters above forecasting launch at 2026, with specific probabilities for go/no-go in each period of time until the product’s launch and followed by the excepted patent period. Values are capitalized as per the valuation date. The main parameter is the attrition rate (volatility), which is based on B&S` equations for project valuation as follows:

We can indicate 8 scenarios leading to product launch according to time to market of the company; each one has its probability, based on clinical trial attrition rates. For example, there is 24% chance for the company to reach the market at 2026 with potential sales of $4.9b with all risks. We assume launch at 2027 until the end of the patent period (2035).

ROV valuation

We then continue to run 8 scenarios of total revenues until patent expiration in 2035.

We then run an NPV evaluation for each scenario also after consideration of R&D costs as describe below:

We now need to fold back all 8 scenarios and discounted valuation of each one according to the parameters described above.

Given the aforementioned parameters, we estimate the total value of this program at approx. $17.3m.

Our valuation is somehow conservative as we use ROV and not rNPV. rNPV in this case will yield higher value as one will chose, in most cases, to value the company as a dream company and will choose, based on our basic optimism in ones of the higher scenarios.

[1] Bogdan & Villiger, “Valuation in Life Science – Practical Guide”, 2008, Second Edition.

[2] NMEs come in two varients; NCEs (New Chemical Entities) classified under NDAs, and biological molecules which are new entities classified under BLAs.

[3] BS model 1973

[4] For more information read Demodaran…..

[5]  GBI research, Leukemia Therapeutics Market to 2018.

[6]  Decision resources, multiple myeloma drug market 2012.