Every decade or so there’s a clear shift in the way that pharma/biotech organizations approach their new product discovery and development productivity challenges. The 90s were marked by investments in combinatorial chemistry and HTS. While many successes were observed with these platforms, stakeholders realized that not enough chemical space could be covered by “full factorial” library designs (and commensurate screening campaigns).
In the early 2000s, with the importance of more targeted lead optimization efforts re-established, discovery teams were downsized with increased outsourcing of specific tasks to regions with lower cost structures. Stakeholders, however, are realizing that an over-reliance on outsourcing creates a gap, specifically with the cross-disciplinary collaboration opportunities that integrated project teams exhibit.
Now, there are increased investments in data sharing/knowledge management and automation platforms. This new cycle of platform investment, for parallel and high throughput experimentation, is applied towards targeted discovery and development; with the added focus on democratic access to these platforms, whereby a majority of scientists use these platforms, thus increasing overall investment ROI.
To calculate platform ROI, stakeholders should assess the total cost of implementation and ownership of these platforms versus the platform scope, scale, and corresponding work product.
For discovery platforms, the key performance indicator (KPI) is the number of development candidates nominated per annum. Platform investments must allow for a comparative decrease in the number of FTEs necessary while maintaining or increasing the number of nominated development candidates.
In development, the KPI is time, specifically reducing the time to develop and produce clinical trial material (along with relevant health authority and institutional review board approval) at a scale required for Phase I trial designs. Traditionally, this time is 12–18 months. Any platform investments must reduce this time.
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