Investment Decisions Based on Product Portfolios: Part 1

The Series

Regulatory professionals are increasingly being asked to provide input on complex strategies related to portfolios of products (which products to keep and which products to advance), and regulatory competitive intelligence (e.g., whether a product is worth advancing given the current or future market environment). They also are expected to provide input to help estimate the probabilities of success related to key milestones in clinical drug development, such as registration (Will the product be approved?). All these roles augment more-traditional regulatory tasks, such as preparing regulatory submissions, representing sponsors at regulatory meetings, determining a sponsor's regulatory strategy and submitting dossiers for registration purposes.

In an era when product partnering is becoming more common, regulatory professionals are being asked to comment on matters related to product development earlier in the development cycle. This input can affect business decisions positively or negatively, which in turn impact the bottom line. For example, the author was asked to comment on the likelihood of US registration success for a particular dual-action product in a class that was otherwise well known. Based on historical discussions with FDA, the data package that was reviewed and discussions with other functional area experts, it appeared very likely that the product would be approved. The author's company invested in the product on a risk basis with returns from sales royalties and it sold very well, thus positively impacting the bottom line.

As in medicine, there is an art to the regulatory science of estimating the probabilities of technical success. It behooves each regulatory professional to learn more about how regulatory outcomes impact business decisions. There is a need to leverage technical expertise (both R&D and commercial) and regulatory experience to better understand the rationale behind making complex business decisions that can impact whether products will be advanced, sold, out-licensed or abandoned.

This three-part series discusses some of the fundamental investment decisions based on the author's experience investing in portfolios of pharmaceutical products-such as how much one can invest (and thus potentially lose) and the palatability of the proposed return structure. The articles break down many facets of this complex process to give the reader insights into business decisions related to portfolios, with the most common situations highlighted.

The series also provides several case examples of these principles in action from the author's experience while serving in the due diligence group of Quintiles, which was rebranded as NovaQuest (2006) and later spun off as NovaQuest Pharma Opportunities Fund III (its brand name as of the second quarter of 2013). The case studies were created using only publicly available information as noted.

Part 1 of this three-part series discusses definitions and boundaries for key investment aspects associated with product-based portfolios, whether the definition entails the number of assets available for partnership or investment appetite.

Part 2 begins with a discussion of boundaries set up by the capital limit of a fund or artificially created boundary (e.g., special purpose entity (SPE)), and whether the portfolio is a group of assets or the goal is to partner on multiple single assets to have a portfolio effect. Part 2 also discusses the feasibility of capital syndication to garner financing for portfolios, and ends with a description of the key differences in portfolio strategy between big pharmaceutical and biotechnology companies.

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Part 3 concludes the discussion regarding the key differences in portfolio strategy between big pharmaceutical and biotechnology companies and covers portfolio management, innovative partnering solution strategies and commercial perspectives.

It is hoped that the series will heighten the reader's interest in matters related to business decision making, with the ambitious goal that our healthcare systems, employers, patients and careers will all benefit from our judicious use of capital in what the author's company terms the "New Health" landscape.

Because some business terms may be unfamiliar to regulatory professionals, a list of terms and acronyms is provided in Table 1.

Introduction

Provision of venture capital equity and other investments in the pharmaceutical industry is risky business. Investments can take many forms, from purchasing stock (or entire companies) through investing in individual products (in development or commercialized). This article focuses on the latter investment option.

Investment groups employ a myriad of strategies to dilute risk. For example, to mitigate the risk associated with a single product asset, an investor group may consider accumulating a portfolio of products. A "product," for purposes of this article, is defined as a small molecule, biologic or medical device.

While, individually, these products may have a high potential for technical failure, grouping them together with other compounds will increase the chance for single or multiple successes. Simply put, with a portfolio of products (a "portfolio" is defined as at least, but typically more than, three products), there is a greater likelihood that capital will be returned from the success of at least one predefined milestone, even if others do not meet certain milestones, such as proof of concept (PoC), a primary efficacy (or other predefined) endpoint, progression to the next phase of drug development, regulatory approval or a certain sales forecast. A commonly used expression describing this phenomenon is "more shots on goal."

Most pharmaceutical companies acquire or develop products with the goal of forming a portfolio. Decisions are based on the company's business model, resources and capabilities. For example, Genzyme, prior to its acquisition by Sanofi, focused almost exclusively on niche, orphan drug products (that allowed for expedited regulatory review and exclusivity advantages) with very high costing models.

This article will not discuss the many decisions regarding acquiring and advancing candidates in a portfolio (usually based on net present value (NPV), driven by commercial considerations), but rather, on the process used by third-party capital providers (e.g., NovaQuest Pharma Opportunities Fund III) to select investment candidates for a portfolio of products.

The two main drivers for consideration by any third party when investing capital in a portfolio are: the magnitude of risk that the investor is asked to take; and the palatability of the return structure to the potential partner. Most deals, in the author's experience, are abandoned or grow cold not because of a flaw in the product or company but because of a factor related to the proposed return structure.

Controlling Risk

Risk for the investor is scaled, with the greatest exposure associated with earlier stages of drug development (e.g., preclinical or Phase 1 drug development). With a few exceptions (e.g., accelerated approval in high-risk settings such as oncology), risk lessens as the product is studied in greater numbers of patients and in later stages of development (e.g., Phase 3 or even postapproval).

Risk also declines due to the portfolio effect, where the riskiness of the total portfolio decreases as more assets are added. In addition, some companies have used other strategies that employ the portfolio effect; for example, creating a portfolio with a sufficient number of assets based strictly on drug development averages (usually either calculated by a due diligence team or using published averages such as those in Parexel's Statistical Sourcebook) as a way to assess the likelihood of hitting a milestone with a basket of early-stage (e.g., Phase 1) compounds. In this type of scenario, a portfolio is created by adding together three or more compounds. As a theoretical example, if the average likelihood that one compound (in a certain therapeutic area) will meet a predefined milestone is 10%, then, by having at least 10 compounds in the portfolio (without "cherry picking" or biasing asset selection criteria) it should be almost 100% assured that at least one of the 10 compounds will meet the predefined criteria.

To further reduce the risk associated with portfolios, companies that provide capital perform due diligence to better understand that risk, with the goal of protecting themselves via contractual language. Due diligence includes a thorough investigation of all available data-both proprietary (after a confidential disclosure agreement (CDA) is signed/executed) and non-proprietary-by a team of experts with the intention of predicting future events (such as the probability of success and the sales forecast). This process aims to equip a deal team to manage risk and execute a favorable financial transaction. All venture capitalists and investment arms of companies perform due diligence prior to investing money in a deal or getting involved in a partnership arrangement.

The due diligence exercise, culminating with a report that articulates the team's findings, should provide capital investors with the positive, negative and unknown attributes of each drug, biologic or device in a portfolio (or proposed portfolio) and the probability of successful achievement of a predefined milestone. This is typically regulatory approval, but milestones can also be defined as meeting the primary efficacy endpoint, advancing to the next stage of drug development or even meeting an artificially created endpoint (e.g., decrease in HbA1c, percentage weight loss, percentage decrease in blood pressure, etc.). Due diligence also can provide an understanding of the sales potential of the product for deals where returns are matched with royalties or where a risk-adjusted NPV of an asset is required.

Return Structure

The due diligence exercise is aligned with the proposed return structure. In essence, only the findings that could potentially affect the return should be reviewed. It is not important to conduct a full commercial due diligence exercise on, for example, a portfolio of Phase 2 assets for which repayment is based entirely on milestones.

Other return structures can be aligned and negotiated based on the perceived risk. For example, if the product is a "me-too" product with a good chance of regulatory approval, the buyer may stake the return to that milestone, whereas the seller may wish to defer a return to a royalty component, which may be less certain (and more risky for the capital provider)-given the strong competition perceived in a class of therapies where there are alternative options for patients.

Another return structure could include a mechanism to decrease the cost of capital (CoC). For example, a common method is using a seller's existing royalty strip to offset the CoC. A "royalty strip," for purposes of this article, refers to an ongoing (usually monthly or quarterly) payment made to a seller from the sales of an approved (and different) product in return for an investment made in an earlier transaction. This existing and expected continued flow of capital can be transferred to the buyer. Royalty strips are usually only a fraction (e.g., <10%, thus the term "strip") of the total sales of a particular product and may be confined to a particular geographic area (e.g., US only, EU and US, Canada only, etc.).

Number of Assets Available for Partnership

There is no ideal number of assets to be included in a portfolio, but for purposes of this discussion, the minimum number is three and the optimal number could be defined as the amount of capital available for such a portfolio (via a single source or a syndicate) or by using more sophisticated statistical models such as Bayesian statistics. Bayesian probability belongs to the category of evidential probabilities and enables reasoning with propositions whose truth or falsity is uncertain. To evaluate the probability of a hypothesis, the Bayesian probabilist specifies some prior probability, which is then updated in the light of new, relevant data. Suffice it to say that, using such techniques, the optimum number of products in a portfolio can be aligned with the risk associated with each asset, with the differing probabilities of success (for predefined milestones) aligned such that the capital provider has very little chance of losing all money invested. In the author's experience, the number of assets usually ranges from four to eight, but could be higher or lower, and is also based on investment appetite (covered below). Additional discussion of Bayesian statistics is beyond the scope of this article.

In the author's experience, many larger companies, mainly through mergers and acquisitions, are sitting on large portfolios of less-strategic clinical assets (e.g., assets that lack allocated budgets or have been de-prioritized for a variety of reasons). They may wish to partner on these assets (to retain the value inherent in the intellectual property should the compound be approved and increase the investment value of each candidate in the next stage of drug development) for the purpose of outsourcing the asset or taking it to the next stage of development. In general, investor groups wish to partner with companies whose available assets are of high strategic value. Lesser-value products may not get the capital or attention of the partner needed to optimize their success.

In the author's experience, some companies want the potential capital partner to take all of the risk for a very large, but typically very unlikely, upside. This scenario, however, does not align interests.

To reduce the risk for each stakeholder (usually the third-party capital investor), it is advisable for the buyer and the seller to invest in a substantial portion (e.g., half) of a program or portfolio. While this may not be an option for certain potential investment opportunities, it aligns partners and ensures that each partner is doing all that it can to optimize the relationship.

Larger portfolios (e.g., with more than three assets) usually are limited by the amount of capital required and degree of risk. For example, a basket of Phase 1 assets would carry very high risk but lower costs, as clinical drug development costs in this phase are much less for each trial compared with those in the later stages of development (e.g., Phase 2 or Phase 3). A basket of Phase 3 trials, for example, given the clinical and efficacy data accumulated to date, would be considered much less risky. However, the typical cost of these pivotal trials would probably make it prohibitive to attract capital from a single source for more than say, three studies.

Risk also may depend upon whether the drug candidate is in a class of compounds with proven efficacy in the disease area being tested or is based on an unproven scientific theory. For example, many new compounds being tested in oncology, Alzheimer's disease and other areas of unmet need have inherently more risks because the cause or the pathway of the disease is not yet fully understood. In contrast, a compound with the same mode of action and therapeutic class as an approved drug would be expected to have a much higher probability of success.

Investment Appetite

Investment appetite is correlated with the degree of capital loss an investor group is willing to risk. No investor group wishes to lose money, but due to the business plan or magnitude of capital available for investment (and thus the ability to diversify), some investors may be willing to take less upside in exchange for the ability to do more deals, while others may need to take a larger upside to satisfy their shareholders and investment committees. In general, the greater the risk the capital provider is asked to take, the larger the expected return. This general paradigm provides the basis for negotiations from the initial term sheet to the final contracting stage of the partnership.

Many deals are not executed for reasons other than a flaw in the product or the company. In addition to a variance in investment appetite, reasons may include: inadequate (or unobtainable) contractual protection; inability to obtain a warrant or representation or the desired accounting treatment; an unsuitable return structure; a future risk that is deemed unacceptable (e.g., a potential lawsuit); or an unreasonable return structure (as deemed by the potential partner).

Capital Boundaries

A "special purpose entity" (SPE), for purposes of this article, is defined as a legal entity (usually a limited company of some type) created to fulfill narrow, specific or temporary objectives. SPEs typically are used by companies to isolate the firm from financial risk. Portfolios can be limited, as mentioned before, by the capital limit of the fund or even the boundaries created by syndication in an artificial environment, such as the SPE.

Most investment groups, by predefined investment criteria, have a limit to the amount they can invest in a particular deal and this limit typically is based on a percentage of the entire fund amount. For example, if a company has a $100 million fund and the concentration (maximum) limit is 20% per deal, it can only invest in only five deals that cost no more than $20 million each, unless they invest in deals of smaller magnitude or are part of a syndication process.

In the author's experience, many companies realize they cannot obtain all the capital required for a large portfolio of products from one source because of internally defined boundaries (which may be driven by profit and loss relief or some other factor). In this case, the magnitude of the limit, for example $250 million, will dictate how many candidates can be accommodated within its boundaries-e.g., fewer Phase 3 candidates and more Phase 2 and Phase 1 candidates.

For companies that provide pharmaceutical services as a form of capital, such as clinical research organizations (CROs), it is important to note that while the Phase 2 stage of drug development presents greater risk, there is also more room for influence, in contrast to the Phase 3 or pivotal stage, which offers less chance of influence (for a variety of reasons including regulatory interactions).