Factoring The "What Ifs" Into Supply Forecasting

Clinical supplies have historically been considered part of the execution phase of clinical trials, instead of a key component of the planning process. Now, growing urgency in the biopharmaceutical industry to speed new products to market is leading to greater appreciation for supply forecasting as a strategic and highly complex success factor.

A supply shortfall can delay the start of a clinical trial or cause an ongoing one to grind to a halt. At the same time, clinical supplies overage can be equally costly. Recent studies have shown that as much as two-thirds of the materials packaged and shipped were not actually dispensed to a patient.

Although seemingly simple, supply forecasting is surprisingly complex. Relying exclusively on a standard mathematical formula for forecasting supply needs, however, fails to factor in all that can go wrong to disrupt a supply chain at a time when sponsors can least afford costly missteps.

Escalating trial costs reflect a steady increase in the volume, length, breadth and scope of clinical studies. The complexity of trials is also accelerating, thanks in part to a spike in studies of biologics requiring special handling and those targeting especially challenging problems such as Alzheimer’s disease, diabetes and cancers.

With such high stakes, clinical trial professionals must take every precaution to prevent the supply chain from unraveling. In addition to modeling, this includes factoring in a host of “what ifs.” Defined as anything that could jeopardize the supply chain, “what ifs” include everything from natural disasters to shortages of commercial drugs used as comparator or standard of care.

Effective supply planning requires decision making that strikes a balance between what’s known and unknown, risk and budget, the needs of the trial and those of patients. The ultimate goal is ensuring that the right patients receive the right drugs at the right time. Otherwise, everyone—sponsors, investigators, patients and society at large—stands to lose.

This paper discusses the aspects to consider when developing a supply plan, the influence of early decisions and impact on outcome as a trial progresses, and how decisions can put patients and the trial at risk.