24/7 BIOPHARMA - issue 1 / October 2024

CPHI REPORT

Figure 1. Data governance framework.

data integrity have moved to the forefront, driven less by compliance and regulatory requirements and more from the need for high quality data to give confidence in our analyses. Whether deployed as pilots or continuing across the value chain, as more islands of targeted innovation emerge, cogent and consistent data management becomes a priority. Data quality is an imperative in formal processes such as data profiling, data hygiene and data obsolescence, and a precursor to deploying data intensive innovations. Such organisational understanding

in a nominal matter (evaluating value assuming success of a project) or risk-adjusted/expected value (evaluating value, including the risk of failure). Today, the risk-adjusted metrics provide a truer measure of an investment’s value. A recent study analysed clinical trial data from 2010 to 2017 and revealed four possible reasons for the 90% clinical failures of drug development: lack of clinical efficacy (40%–50%), unmanageable toxicity (30%), poor drug-like properties (10%–15%) and lack of commercial needs with poor strategic planning (10%) 5, 6 . Addressing any of these root causes would affect the cost and time required to bring a new product to market. By considering the impact of an innovation or novel approach to a drug development problem in terms of its ability to improve the risk profile, impact to the risk-adjusted value (expected IRR, expected ROI, eNPV) will show a significant improvement. However, nominal NPV analysis will not show the impact of these risk profile improvements, which can shift decision making, the success criteria, away from innovation technology and reduce future value. The impact would be fewer programs in the development funnel with the remainder having a higher probability of success and better-funded as the existing budget is reallocated across the remaining programs. If done correctly, this would also translate to more product launches as we look to move the needle on the 12% acceptance rate to market. The principle is illustrated in figure 2. Thinking outside the box, there are several areas in our drug development lifecycle where technology in its current state of maturity could bring greater insight into the potential for success of a program:

is the foundation for evaluating and accelerating the process while providing confidence in the results obtained.

Complementary strategies for drug portfolios

Some reasons the pharmaceutical industry lags other industries in adopting potentially impactful innovations range from lack of clarity in strategic leadership and communication, to cultural resistance, poor change management and regulatory risk aversion. Adoption would be easier if the success of pilot evaluations shifted from technology or methodology assessments to improvement analysis by identifying early program failure modes. If it were possible to screen out safety or efficacy issues earlier, the probability of a later stage program being successful could go up substantially. This would help drug sponsors manage their portfolios more effectively and invest in programs with a real chance of reaching the market. Setting a framework to evaluate a technology or adopt a new approach in drug development requires calculating a pilot project’s potential value in relation to its cost. Metrics such as internal rate of return (IRR) or return on investment (ROI) directly measure the amount of return relative to the investment’s cost. On the other hand, net present value (NPV) measures an investment’s value through its lifetime discounted to today’s value, but does not allow comparison of the level of investment between projects. All these metrics are commonly used by drug development portfolio managers to determine which projects will be more valuable, with NPV being the most common metric. These metrics can be used either

79 TWENTYFOURSEVENBIOPHARMA Issue 1 / October 2024