Episode 8.

Last week at the local tailor shop, I was presented with the ecological argument to purchase a custom-made shirt: “The fit is impeccable, and instead of making 3 shirt sizes (Small, Medium, Large) to sort-of fit your body, a single shirt will be made. Less time, less energy, less waste.” I’m a common 16.5-32 slim-fit-shirt guy, so I walked out without the $150 tailored shirt, but with a useful analogy…

My team specializes in custom-designed preclinical studies. “Bespoke”, “Unique”, “Personalized”. All impressions generally associated with high prices. But is that really true? Certainly, we’d like to think we sell services at premium prices, but the accountants might beg to differ.

Let’s say I need to know if my positive inotrope drug candidate produces short-term benefits in heart failure. (Think of a patient with dilated cardiomyopathy, for instance.) I need one study to get a dose-response curve against cardiac function + one study for potential effects on pulmonary perfusion and ventilation + one PK study to determine elimination rates and establish my dosing regimen, etc…

When designing a “Custom” study to for the same purpose, I’d use implanted telemetry to measure hemodynamics and ECGs, add respiratory monitoring by plethysmography, saturation for gas exchange, blood sampling, body weight measurements. I’d run the study over 7 days of repeat dosing rather than 24 hours only. We’ll get data on the primary pharmacology of the test article, its potential adverse effects on respiration and cardiac electrophysiology, its pharmacokinetics and elimination rate. For 1.5-times the price of a standard dose-range-finding efficacy study, the same 9-12 animals will have covered 4 or 5 individual studies.

The savings in time, money, resources and the adherence to the 3R principles for animal use in research (Refine and Reduce, here), are obvious. So why don’t we do this more? 

For starters, there are the apparent savings associated with “Standardization”. Decreased risk of errors, specialized (rather than polyvalent) staff, predictable outcomes and durations, repeatable price structures. All valid points, accounting-wise. And from a regulatory point of view, one understands the necessity to compare apples and apples for new innovative drugs.

As a scientist -not an accountant- I think it’s lazy: Not having to think outside the box. We know what information is needed to bring a drug from Lead Selection to IND filing; we can at times build innovative study designs, uniquely fitted to a single development program, to generate the data required and minimize the resources and time involved. Efficacy pharmacologists do it, investigative toxicologists do it, and I’m encouraged to see safety pharmacologists and more scientists are designing those wonderful, unique studies.

A “standard efficacy study” is an oxymoron: each efficacy study investigates a unique disease, with a distinct set of symptoms. Take cardiac infarction, for instance: cardiac output is down 20 mL/min in a rat, LV ejection fraction decreases by over 45%, but breathing is unchanged, as is the gain in body weight. In contrast, idiopathic fibrosis in the lungs causes significant changes in lung compliance, but little change in cardiac PV loops. Each efficacy study calls for a customized set of endpoints.