All stakeholders involved in the development, licencing, and market access of health care technologies use stage-specific valuation matched that integrates risks and outcomes to inform their decision making. A stage-specific valuation method, based on defining future cash flows for a product that are success-rate probability adjusted prior to being discounted with a risk rate, is termed risk-adjusted net present value, and a negative value indicates that a loss will be made and therefore the product should probably not be developed. However, values exited from these calculations can be highly variable depending on the data used to generate the calculation, and in light of the estimated $2.6bn in capitalised costs that is necessary to move an innovation to market, without any guarantee of product reimbursement, the financial risk is very high. Indeed recent return on investment numbers for life science investment are staggeringly low, significantly lower than the weight-adjusted cost of capital, implying healthcare R&D is economically unattractive. The outcome is that the objectives of modern intervention R&D are more linked to moving risk off the books or downstream to larger companies, which at face value seem better positioned to develop the products further, when in fact a complete reconfiguration of approaches, models and realistic actions and strategies are likely to generate more value. As NPV calculations are only as good as the data used to generate it, and both accurate and comprehensive values ideally should be used, based on real market dynamic, the latest clinical success rates and considering the latest reimbursement approaches, more formal HTAs for therapeutic intervention, we reassessed valuation approaches, integrated the reality of later stage clinical validation, product reimbursement based on Health Technology Assessment perspectives, and downstream costs to generate a whole value chain calculation. The outcomes led us to consider an alternative risk rate model based on dynamic changes that occur throughout the R&D process. While modelled for medical intervention development, the outcomes of this work can also be applied for evaluation of diagnostics and medical devices. Using four intervention types in two diverse indications as a model, we simulated various valuations, and our analyses suggest that using indication-specific success rates provides a more accurate value determination, and that a different risk rate approach should be followed, which was further validated using real market data. The implication is that all stakeholders need to take a holistic approach to valuation and working together for mutual benefit to de-risk development programmes and pipelines. This will enable all of them to use the same values before and throughout the R&D process, and facilitate better decision making, clearer trust as the innovation changes hands up the value chain, and eventually better and more cost-effective therapies.
