Royalties challenge risk and reward in AI drug development

By Ulrik Kristensen, PhD, The Science Advisory Board contributing writer

June 3, 2021 -- As artificial intelligence (AI) becomes increasingly important for drug development, how should AI firms -- many of which are small startups -- structure their business relationships with pharmaceutical companies?

Many AI firms are turning to royalties on future drug sales as an alternative to licensing or consulting fees, which are widely seen as favoring drug developers. While no means a new phenomenon in drug development, royalties on sales will play a bigger role and drive new market dynamics throughout the pharmaceutical industry.

In the following article, I will discuss the diversification of revenue streams in the context of the wider pharmaceutical industry and relate this to the development stage of individual AI startups.

The right sales models for AI

Developing the right sales models for AI drug developers has always been a challenge. A typical software as a service (SaaS) license fee model has proven unsuitable, as it doesn't adequately capture and reflect the potential value for the client. On the other hand, individual one-off consulting fees lack the risk-sharing component necessary for high-risk projects with long timelines for measuring success. This has created a complex and ever-evolving deal composition.

Although the dominant sales model now is a partnership model with initial payment and milestone payments dependent on the success of the molecule in clinical development, there is no one-size-fits-all. Deals are highly dependent on the specific project, the client, the financial situation of the AI specialist, and the trust in a successful outcome from both the client's and the AI specialist's perspective.

Ulrik Kristensen, PhD.

For the early-stage AI drug development startup, the first paid deals are typically one-off projects on a consultative basis, as some income helps convince investors that the algorithm works and there is business potential. These initial deals are typically with small and midsize pharma and biotech companies, and the sizes of the deals are equally modest. As the company grows, partnership deals are typically initiated, and initial payments gradually develop into milestone payments for successful projects.

Once the AI specialist has proven successful in the first few partnerships, the opportunities for larger deals with leading pharmaceutical companies are chased. However, although the size of these big pharma partnerships are making headlines in the media, the proportions of the initial payments are often small compared to the total value of the deals.

As the AI startup matures, the need to take on further risks increases considerably, as the majority of the revenue becomes success-dependent milestone payments.

The longer you wait, the more you get -- probably

Sales royalties and asset ownership offer yet another income source for AI specialists with the financial backing to engage in long-term deals with considerable risk.

To obtain asset ownership in larger deals with pharma is notoriously hard, but royalties on pharmaceutical sales are becoming a crucial component in larger partnership deals. For the pharmaceutical company, these royalties decrease risk even further and delay a proportion of expenses until an actual revenue is generated from pharmaceutical sales. Many pharmaceutical companies are therefore willing to pay considerable money for such de-risking deal structures.

For the AI specialist with financial backing to engage in long-term deals, the reward can be significant. However, skills in providing a precise evaluation of future sales in highly competitive and changing markets is required, as is securing sufficient financial backing and cash flow in the extended period from deal to payment. Getting the right balance between short-, mid-, and long-term revenue, aligned with the startup's stage in development, is therefore essential.

Putting too much emphasis on asset ownership and royalties early in business development can cause an unhealthy balance and a dependence on investors without convincing financial mastery, a situation that can turn fatal for any company.

On the other hand, asset ownerships and sales royalties can also drive bigger funding rounds, as the prospects of considerable future income attracts long-term investors in the industry. Preparing early for diversified revenue streams is therefore important.

What this means for the AI ecosystem

With more than $9.2 billion total investment in the industry and numerous big pharma partnerships established in recent years, many AI specialists are now prepared to take on additional risk in return for potentially highly rewarding royalty deals.

Turning the risk lever further toward the AI specialist -- with more emphasis on royalties -- will drive more deals with small and mid-sized pharmaceutical companies and early-stage biotech companies. The prospects of benefitting from AI partnerships in return for sales royalties with delayed payments will attract clients with tighter budgets and funding-dependence, as the typical clinical milestones would offer no immediate income.

Over the longer term, royalties on sales will increase the potential market size for AI in drug development, as a larger proportion of the revenue will be from outside the pharmaceutical research and development expenditure and clinical development accounts. This will help drive larger funding rounds in the industry in the shorter term, especially for vendors with a healthy mixture of diversified revenue streams.

The ability to seek royalty deals requires sufficient financial backup for AI specialists. Royalty deals will therefore favor more established vendors able to take higher risks, and consequently fuel further consolidation in this highly fragmented industry.

Ulrik Kristensen, PhD, is founder and principal analyst at Emersion Insights.

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