Option pricing to evaluate and decide on Pharma pipelines

Pharmaceutical R&D projects often involve numerous uncertainties, including technological feasibility, regulatory approval, and market acceptance. Traditional project evaluation methods often fall short in effectively addressing these uncertainties.?

24 years ago, having freshly joined Pharma after business school, Banking and Physics, I was part of a project to use option pricing and Black-Scholes models to help us make more informed decisions about pharma pipelines. Yet it seems to never really have picked up. Is now the right moment?

What are Option Pricing and the Black-Scholes Model?

Options are financial derivatives that provide buyers the right (but not the obligation) to buy (call option) or sell (put option) an asset at a predetermined price before a specific date. The value of an option depends on several factors, including the price of the underlying asset, the strike price, the time until expiration, and the risk-free rate of return.

The Black-Scholes model, developed by economists Fischer Black and Myron Scholes, is a mathematical model used for calculating the theoretical price of financial options. This model considers variables such as the current price of the asset, the time to expiration of the option, the strike price, the risk-free interest rate, and the asset's volatility.

How do we apply them in the Pharma and Biotech industries?

Pharma R&D projects share several similarities with financial options. They require an initial investment with a known cost but offer potential future benefits with unknown value, both of which are influenced by several risk factors.

When considering a pharma pipeline, each stage (such as preclinical trials, Phase I/II/III clinical trials, and market launch) can be seen as a call option. The investment needed for each stage is equivalent to the option's exercise price, while the possible payoff from successfully progressing to the next stage represents the underlying asset.

For instance, when a Biotech company decides to progress from preclinical studies to Phase I trials, it essentially "exercises" its option by investing additional resources. If the trial is successful, the value of the project increases, making the subsequent option (moving to Phase II) more valuable. However, if the trial fails, the firm can abandon the project, much like an option holder letting an option expire worthless.

…and what are the benefits of this approach?

This option-based approach allows stakeholders to evaluate the project in terms of the option’s intrinsic and time value, taking into consideration not only the project's immediate expected profit but also the value of future options (i.e., the option to proceed or abandon at each stage).

Moreover, using the Black-Scholes model, pharmaceutical companies can quantify the potential value and risks associated with different pipeline projects, facilitating more data-driven and effective decision-making.

By examining each R&D stage as a series of call options, companies can also better manage their risk and potentially prevent costly failures. For instance, a firm may decide to not exercise an option (not proceed to the next development stage) if the strike price (the cost of further investment) exceeds the perceived value of the underlying asset (the potential return from project success).

So, why has option pricing not been used more in Pharma and Biotech?

The use of option pricing theory and the Black-Scholes model in the pharmaceutical industry has been limited for several reasons.

1.?????Complexity and lack of expertise?

The Black-Scholes model and option pricing theory are complex financial tools that require a deep understanding of finance, mathematics, and statistics. Many pharmaceutical companies lack the necessary expertise to effectively use these tools. The implementation of these models also requires a significant amount of data and computational power.

2.?????Assumptions of the models?

The Black-Scholes model assumes that the price of the underlying asset follows a geometric Brownian motion, that the risk-free interest rate is constant, and that there are no transaction costs or taxes. However, these assumptions may not hold in the context of pharmaceutical R&D projects, making the model less applicable and potentially inaccurate.

3.?????Uncertainty and variability in R&D

Pharmaceutical R&D projects are highly uncertain and complex, with a multitude of factors that can influence the outcome of the project. These include technological uncertainty, regulatory risks, and market acceptance, which can be hard to quantify and model accurately.

4.?????Focus on traditional valuation methods

Pharma companies often rely on traditional project valuation methods such as Net Present Value (NPV) and Return on Investment (ROI). These methods are simpler and more intuitive to use, and thus may be preferred over the more complex option pricing models.

5.?????Lack of standardization

There is no standard way to apply option pricing to R&D project valuation, which can lead to inconsistent results and interpretations.

Ok, but nevertheless…

…despite these challenges, the use of option pricing and the Black-Scholes model can offer significant benefits in terms of more accurately capturing the value and risks associated with pharmaceutical R&D projects. While these tools may not replace traditional valuation methods, they can serve as a useful complement, providing a more comprehensive view of a project's potential value. Increased awareness and understanding of these tools, as well as advancements in technology and data availability, may facilitate their broader adoption in the future.

…and so, what is different now? Artificial Intelligence!

AI has the potential to significantly accelerate the use of option pricing and the Black-Scholes model in the pharmaceutical industry. Here's how:

1.?????Handling Complexity

AI, and particularly machine learning and deep learning algorithms, can handle complex datasets and identify patterns, correlations, or trends that us humans might overlook. AI can help to break down the complexities of the Black-Scholes model and option pricing, making them more accessible and less daunting.

2.?????Prediction

AI algorithms are excellent at making predictions based on large amounts of data. These predictions could be used to anticipate the success or failure of a drug at each stage of development, which could then feed into option pricing models to calculate the potential value of a project.

3.?????Automation

AI can be used to automate the process of applying these models. Instead of having to manually input data and calculate values, pharmaceutical and biotech companies could use AI to automate these processes, saving time and reducing the risk of errors.

4.?????Enhanced Decision-making

By integrating AI's predictive capabilities with option pricing models, pharmaceutical companies could enhance their decision-making process. AI could provide real-time insights into the likely success of a drug, the estimated costs, and the potential return on investment. This could lead to more informed decisions about which projects to pursue and which to abandon.

5.?????Improvement Over Time

AI models, especially machine learning models, can improve over time as they are exposed to more data. This means that the accuracy and reliability of the option pricing and Black-Scholes models could improve over time as the AI learns from more project outcomes.

6.?????Dealing with Uncertainties

One of the key challenges with pharma R&D is dealing with uncertainties. AI and machine learning algorithms, particularly those built to handle uncertainty like Bayesian networks or Monte Carlo simulations, could help to better quantify and manage these uncertainties.

However, let us be realistic…

…and note that while AI can significantly enhance and accelerate the use of option pricing in pharma, it's not a silver bullet. The quality of the output is highly dependent on the quality of the input data. Furthermore, these AI models also require a high level of expertise to build, train, and interpret correctly. Nonetheless, with proper implementation and management, AI could play a significant role in the broader adoption and effectiveness of option pricing in the pharma industry.

Summing it all up, ...

...option pricing and Black-Scholes model provide an innovative and sophisticated method for evaluating pharmaceutical R&D projects. By considering each stage of a pharma pipeline as a series of options, these financial models enable companies to better quantify risks, manage their investments, and maximize the value of their pipelines.

While these models cannot eliminate all uncertainties associated with pharmaceutical R&D, they offer a powerful tool for firms to make informed strategic decisions. Given the significant investments and high stakes involved in pharmaceutical development, adopting such advanced valuation methods can potentially lead to more efficient allocation of resources and ultimately improve the odds of bringing innovative and valuable drugs to market.

With AI at our finger tips and within reach, can we finally fully leverage these powerful financial tools and models to make Pharma and Biotech development more effective? Seems very possible!