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Optimising biotech trial designs to stretch your cash runway

The shape of the global funding landscape has fundamentally altered in 2022. Early stage and innovative biotech companies are not immune to this funding shock and must optimise trial design at the earliest stages to maximise their available capital.

Novel drug development is a costly endeavour. The biotech sector has recently benefitted from a wellspring of investment options. But within the last year, the funding market has become highly competitive, and biotech companies are not immune to it. According to S&P Capital IQ, the global biotech sector has taken a serious hit, falling more than 70% since the high mark in 2021. Biotech is more vulnerable to this cashflow downturn as they are inherently riskier businesses that rely on heavy investment through several funding rounds with financing linked to discrete program milestones. Without funding, they fail, obligating biotech companies to stretch their cash across the development process to reach the next milestone. Clinical trials are the most significant expense that biotechs incur, and optimising trial designs through early engagement offers a potential opportunity to maximise return on investment. This article outlines a few early engagement considerations for trial design optimisation. 

Choose the right design

Trial design needs to be appropriate for the stage of development, understanding that the approaches used for proof of concept may be different to the approaches required for a confirmatory study that needs to meet full regulatory rigour. Often, interim analysis can be built into the design which may be used to make early decisions on futility or success. Traditional study designs can include these interims, although adaptive designs can provide greater flexibility around the timings of go/no-go decisions, particularly in early development. The growing interest in home health and remote assessments has led to the rise in decentralised and hybrid trials, which may offer tangible benefits across many therapeutic areas if planned and implemented correctly. The bottom line is to ensure that the study is appropriately designed to test the key hypothesis without being overly complex, which can impact regulatory review, site and patient interest and ultimate decision-making. Evaluate the available methodologies to identify costly risks and challenges that may arise in the implementation of the trial and select the model that suits both the program goals and budget. We have helped hundreds of clients design the best-fit trial, and in a recent case study, ICON assisted a sponsor with strategic development planning for a lean organisation with minimum infrastructure. ICON identified opportunities to improve the development plan, including streamlining protocol, that reduced overall outsourced spending and dramatically extended the project’s cash runway.  

De-risking design

Choosing the best-fit trial design and methodology goes a long way toward stretching funds, but there are always risks to mitigate, especially for smaller biotech throwing all their resources behind an asset. Whether you are a nascent biotech or large pharma company, the clearest way to de-risk complex development programs is by leveraging a two-fold approach when considering trial design: detailed endgame planning and failing faster in the short term.

The first approach, detailed endgame planning, entails thoroughly defining the eventual label, working backwards through the reimbursable Target Product Profile (rTPP) and detailing the associated Clinical Development Plan (CDP). The rTPP is a roadmap for the overall development strategy, pricing and positioning for the asset and helps you to navigate interactions with regulators, payors and partners. When developed and utilised early, it is a dynamic tool for analysing the different development pathways based on costs, schedule and ultimate value. A comprehensive rTPP also provides opportunities to assess design for accelerated evidence generation or even the strategic delay of specific components.

Identifying the most appropriate target patient population for the stage of development should be conducted as part of the TPP development and can also mitigate risk. Often, trials have targeted a large patient population, making it more challenging to detect significant indications. Designing the trial with smaller patient populations within a subset of a disease or therapeutic area and more precise indications can accelerate the program and demonstrate more significant effects. Conversely, opting for a smaller subset of disease poses alternative risks: it decreases the patient pool which can cause recruitment challenges, it requires a higher degree of certainty that the selected population will respond and it requires sufficient data to warrant a design based on the biological plausibility of the mechanism rather than more exploratory designs. De-risking your design necessitates a customised approach. Consult experts familiar with these specific therapeutic areas and have extensive experience optimising designs.

The second approach to de-risking the design is by failing faster, which simply means designing the trial so that ultimate success or failure can be determined at earlier points in the process and with absolute clarity. Designing trials beyond a success/failure binary, but with success in mind, allows for key learnings about your asset at every stage, even in failure. With funding more difficult to obtain, trials should hedge against burning through cash stockpiles by exploring interim analyses and establishing rigorous go/no-go strategies. Consider what data would strictly signal success or failure at strategic points early in development and design your trial in such a way that each step provides clear information on the viability of continuing and avoid betting everything on an unachievable long-term goal.

Early engagement with the right partner

Biotech companies tend to run lean. With additional funding pressures, it becomes imperative for biotech to choose similarly agile, expert partners for the development process to optimise their return on the outsourcing investment. Early engagement with consultants or a CRO enables the development of strategic, flexible approaches that maximise resources and efficiency to optimise the trial design from step one. ICON routinely engages with companies 12-24 months prior to starting clinical trials to advance regulatory engagements, estimate programmatic development costs and optimise study designs. Partnering with a CRO that provides end-to-end services ensures the seamless transfer of institutional knowledge and insights across the development continuum. It also enables a more intelligent design to maximise opportunities for cost-effectiveness. ICON, for example, is experienced in biotech asset development and has 8,000 dedicated biotech specialists in-house ready to support the project with tailored solutions.

Conclusion

The biotech funding market has taken a recent downturn from the high mark of 2021 and has left biotech companies with fierce competition over fewer funds and less appealing deals to move their innovations forward. With this volatility, biotech must be deliberate about cost-effective design and developing creative solutions. The long clinical trial process is the biggest cost to most biotech companies, but it also offers an opportunity to stretch the cash runway. Early engagement with an end-to-end partner enables a holistic approach to optimising trial designs. ICON can offer flexible, custom solutions at any point on the development continuum, but early-stage involvement allows for additional opportunities to maximise available funds.

For more information on how ICON can assist in optimising your trial design to suit financial constraints, contact us or read our blog on improving your funding pitch.

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