Wouldn’t it be nice if there were a crystal ball that could predict, during the very early stages of drug development, whether a new medication would represent good value for money at its intended launch price? Or which efficacy targets it needed to hit in order to remain cost-effective? Or what an assessment by the Institute for Clinical and Economic Review (ICER) might look like? Unfortunately, there’s no crystal ball that can perfectly do this, but there are tools that can help; enter early-stage economic models.
Traditionally, we hear about economic modeling when an innovative drug is nearing its launch date. This type of late-stage modeling is typically used by pharmaceutical companies and health technology assessment agencies to estimate the clinical and economic effectiveness of new therapies. These models use data from Phase 3 clinical trials, open-label extension studies, and retrospective database analyses which target the utilization and costs associated with different healthcare resources.
In contrast to late-stage models, early-stage models typically come into play pre-Phase 3, utilizing clinical data from pre-clinical, Phase 1, or Phase 2 clinical trial results and economic data derived from the literature to inform model design and parameterize the inputs.
Figure. Where does early-stage modeling factor in?
The implications of modeling an intervention’s clinical and economic benefit during the earliest stages of development are three-fold and can help manufacturers:
Common early-stage modeling use cases include:
Additionally, early-stage models can be designed based on the underlying disease epidemiology and standard of care, making these models extremely flexible and adaptable when new treatments emerge on the market or when Phase 3 clinical trial data is available. Economic parameters for early-stage models are also typically derived from the literature, meaning models developed early-on in the product’s lifespan could be beneficial in highlighting key data gaps and the types of real-world evidence generation that might fill those gaps.
The main benefit to early-stage modeling is in the preparedness that these exercises achieve. Early-stage models are an important source of information, contributing to decisions on the commercial viability, estimated revenue potential, and future development of therapeutic interventions. These models assist with early pricing strategy, Phase 3 clinical trial design, and product positioning (e.g., line of therapy).
One study estimates the cost of research and development for one novel drug in today’s market at $2.6 billion Assuming this, the potential return on investment for incorporating early-stage modeling into a novel drug’s pricing portfolio is huge and could save a life sciences manufacturer a large amount of money.
As the shift towards value-based care continues to focus on pharmaceutical and medical device interventions, using data to inform drug development earlier and more strategically is vital. In lieu of a crystal ball, my vote is for early-stage economic models. Stay tuned for my next post, where I’ll dive into the “Four Ways to Use Early-Stage Models for Efficient Drug Development.”