It’s beyond obvious that the systems being used to allocate academic research funding are not carrying the weight of the system as it currently exists. We recently wrote about the high costs of grant applications, the sources and uses of funding for academic research and the business models used in an attempt to build an academic engine of capitalism within the university ecosystem.
It has also become clear that research intensive businesses struggle to find sustainable sources of research funding both within their organisations and through external sources.
Against the backdrop of emerging trends in the research sector and the increasing politicisation of research, some interesting financial models have emerged. This paper examines novel approaches to financing research risk.
Structured Debt
The InnovFin Infectious Diseases Finance Facility provides loans on terms that require repayment only if a drug is successfully developed (on terms that require contributions from other stakeholders).
This model recognises that:
- research and development is an indispensable part of the healthcare sector, but it also comes with risks that present financing challenges
- experienced government intermediaries can bridge this financing gap.
InnovFin expects to fund EUR24 billion in debt and equity instruments over its 7 year approved funding period, and this is expected to leverage up to a further EUR48 billion of overall research and innovation funding, implying a leverage ratio of 2:1. The European Investment Bank forecasts indicate that if this funding is used as an anchor, it has potential to achieve a 5:1 leverage ratio.
The mid-term report on performance indicates that it is too early to tell whether this financing will fill the gap, but identifies that it is a model that brings cohesion to what is otherwise a fragmented group of small actors.
Given the magnitude of the infectious diseases challenge it seeks to address and the limit of EIB funding available, this capital represents a meaningful stump. However leveraging it is critical to achieving the objectives of the fund.
Other examples of structured co-investment models for research investment include the EUR90 million funding for rare diseases research, announced by the European Commission, the details of which are expected early this year.
Play or pay
A controversial proposal that came out of The Review on AntiMicrobial Resistance was the raising of a $12 billion pot that would be financed by a surcharge levied on the overall sales of pharmaceutical companies that were not developing new drugs.
The response from industry was to express reasoned outrage that a stick would be wielded in an environment that is far more accustomed to lobbying for the carrot. The debate continues around push or pull. Both sides are calling for greater discussion and collaboration.
Each sees potential for leverage in the other’s resources and sees that more can be done to invest it in common objectives.
Regardless of whether this proposal survives the discourse, the levers being applied to foster risk are becoming more intense. Consortia are forming amongst competitor groups to tackle challenges that exceed the risk tolerance of any single actor. The ability and willingness to combine resources, exploit complementary know-how, and internalise R&D externalities is increasing.
Call Options
While the majority of structuring discussions centre around whether a push or pull model should be pursued, options have been identified as a hybrid that could make use of the features from both models.
Call options have been modelled as a meaningful option for vaccines, antibiotics and orphan candidates.
Essentially, the model allows the purchaser to make payments during the early stages of development in exchange for reduced future prices on any product that makes it to market. It could be an effective mechanism for early investment and risk sharing while maintaining a credible purchase commitment and incentives for companies to ultimately bring new antibiotics to market.
On this model:
- portfolio managers would examine research proposals and buy options (paying premiums that would be used to fund the research) with full visibility and interests in the underlying intellectual property; and
- if the research proves promising either directly (leading to an exercise event that allows the option holder to buy the product at a discount) or indirectly (because it has led to related research that leads to that outcome, leading to a recognition payment falling due) the instrument is effective to bring finance to early stage research.
The viability of this model depends on:
- how well informed the quantitative analysis for setting the premium (high enough to fund the research);
- forecasting the ultimate direction of the research and the price at which the resulting product will meet the market;
- the discount that should be reflected in the strike price; and
- the qualitative assessment of the candidates included in the portfolio.
A multidisciplinary evaluation group is required as it is possible that promising drugs might be conceived by companies ill-equipped to carry through their development (in Australia, 65% of biotechnology companies are SMEs with a single candidate, small team and very tight liquidity). For such a team to be effective, full and prompt disclosure of research would be a mandatory requirement for participants. Any governance model would need to assess the research at its design phase and compel disclosures in order to overcome information asymmetry between research teams and their backers.
Rapid improvements in machine learning are aiding in risk assessment to the point where data predictions are offered as to probability of success at critical steps in the drug development lifecycle. With these analytics, it is possible that new markets in derivatives will accommodate risk offsets in ways consistent with those adopted in other parts of the financial markets.
Given drug development has bespoke attributes, including that the failure rate is not evenly distributed, portfolios would need to be sized to persuade investors that the jackpot sits within the group.
By contrast, structuring portfolios of candidates in this segment of the research sector stands to offer diversification that and risk management at levels greater than those which can be achieved through alternatives in the public markets, such as the trend toward the productless IPO. Whilst diversification can be achieved through these offerings, speculators could improve their risk exposure by integrating these tools.
Securitisation
The funding structures outlined above great new opportunities to consider broader dissemination of financial risk in research. Financial structures, such as those that the team at the MIT Laboratory for Financial Engineering, have worked up analysis supporting the use of securitisation vehicles for such purposes.
Equity
Opinions vary as to whether debt is a suitable form of financing for research. Research suggests that intangible assets are accepted as collateral in supporting half as much debt as tangible assets.
In its review of optimal R&D financing structures, the team at MIT have suggested that equity linked products may better serve R&D. In doing so, an outline of a structure that takes account of the characteristics of the sector (being large capital outlays, long gestation periods, high upside, and low probabilities of R&D success).
Regulatory Hedges
Structured risk shifting in the R&D pipeline can provide valuable liquidity attenuation outcomes for R&D intensive businesses. It is becoming clear that solutions to the grand challenges of our day require participants from policy, regulatory and financial communities to integrate more closely with their scientific counterparts.
The MIT concept would allow drug development companies to share risk with the capital markets on the basis of an option that would pay out in response to a trigger event (being the failure of a specific drug in the FDA approval process). This concept is familiar to the contingent valuation rights used in M&A deals (which pay sellers on the occurrence of an underlying corporate event), which can be traded independently of the obligations to which they attach.
The instrument is recognised as being potentially useful for portfolio diversification, given past drug development pipelines to approval appear to be uncorrelated with the broader market or other factors. It also has potential for application outside the health sector. Insurance products in new risk categories appear to work toward similar risk allocations. Whilst this work represents a means of sharing risk in the development cycle, its limitations are recognised in that the pattern of data it uses to generate risk profiles is loosely correlated and generated from a baseline that is idiosyncratic.
Accounting optimisation
A recent review by the UK treasury included a finding that IAS 38 Intangible Assets (Current International Financial Reporting Standards) does not allow capitalisation on internally generated intangible assets. That accounting standard provides that intangible assets cannot be recognised on the balance sheet until it is probable that there will be future economic benefits and the cost can be measured reliably. When costs are expensed in the year and not capitalised, it can be hard to recognise that an intangible asset has been created.
This accounting standard could explain, in part, an underreporting in discovery. The use of collaborative research tests the limit of this standard being applied to expense research costs.
Better identification and translation of intangibles is estimated to have the potential to generate at least £5 billion in financial, economic, and social benefits per year.
Structured collaboration with industry could support this translation.
Efficiency Dividends / Success Fees
The world’s first social impact bond (SIB) was conducted at Peterborough prison in the UK, in an experiment in testing whether structured finance could be deployed to improve socio-economic outcomes related to recidivism.
Whilst the investors received a success payment on that bond, it is acknowledged that much can be learned from that exercise. The pace of learning and improvement has been rapid.
SIBs combine outcome-based payments and market discipline. They are designed to raise private capital for programs in fields that are suitable to being funded by governments on an outcomes basis.
In the context of extreme waste in the grant system SIBs offer the potential to combine improved traffic control with efficiency savings that could be better deployed in support of research.
Prizes
Challenge based innovation is an attractive prospect for organisations in both public and private sectors. They are evolving rapidly and offer a basis for governments, industry and academics to combine efforts to solve problems. SBIR (US), SBRI (UK), Xprize (US), the Small Business Innovation Research for Defence (Australia) are among the many examples of challenge based opportunities for research to take part in problem solving. For researchers, this structure puts the reward in place after the work has been done, and moves the jackpot payment from the licensing phase to the reward for winning (in both cases, these are not sustainable sources of revenue for the research sector, however in the prize scenario, the commercial negotiations around the structure of a license are not the responsibility of the winning researcher).
Some of these prize based opportunities are suitable candidates for support in the form of research risk funding. Considering opportunities to inject external capital into teams working to win these prizes is a potentially interesting means of research risk exposure and support.
There are a number of emerging alternatives to traditional publicly funded grant based financing for research. Designing structured solutions for integrating them, and applying them toward compatible research projects and programs is a challenge that requires a robust governance structure.
Sign up to Coalfacer to learn more about integrating structured finance into academic-industry research partnerships.
