A recent analysis of drug development success rates from Phase I to approval found that the average infectious disease drug is 10 times more likely to succeed compared to the average oncology drug (a complementary analysis here– different magnitude, same directionality). Why?
In our opinion, highly accurate dose selection makes the difference. In a recent JAMA analysis of drugs that failed to receive FDA approval, uncertainty around dose selection was the most frequent driver of the outcome.For the antibacterials field, a highly refined and accurate dose selection process is a huge asset that is not well appreciated as a way to significantly predict and de-risk a Phase III outcome.In our view, antibiotics drug developers and investors alike benefit greatly from a thorough analysis of dose selection ahead of investing time and capital in a clinical trial. We outline the basics and some key questions investors and trial sponsors alike should ask of the process with some help from the experts.Bugs don’t lie: the antibacterial field’s unique tools to de-risk clinical developmentMuch like driving a car benefits from a fuel gauge you can trust, clinical development benefits from a marker that accurately predicts how levels of drug over time impact activity against disease. Antibiotics offer one of the strongest markers around - we can observe in a dish and in predictive animal models changes in bacterial burden that directly drive our patients’ clinical outcomes. This powerful marker supports a process for predicting efficacious doses in Phase III with high fidelity based on human pharmacokinetics (PK) and pharmacodynamics (PD) as well as good preclinical models.
The process works! A picture from our colleague Paul Ambrose and his team speaks louder than words (Paul and his team go into the nuances of dose selection in an excellent white paper here). The analysis looks at dose selection analysis versus approval over several decades to measure the predictive power of PK/PD analysis. Bottom line is – the more likely a drug’s dose is predicted to meet or exceed the level needed to kill bugs based on the four step dose selection process, the more likely it ultimately gets approved.
Fidelity of dose selection based on preclinical and Phase I data depends exquisitely on an understanding of a drugs behavior at the site of infection. Much of PK/PD modeling is based on serum levels; if a drug has a hard time getting from serum to the site of infection (drugs with bioavailability challenges for example), one will have to account for this downside beyond what the modeling predicts. Conversely, drugs present at very high levels at the tissue site relative to their serum levels may have efficacy upside beyond the predicted required dose. Also, although most antibiotics are either time or concentration dependent, some antibiotics will be best dosed in ways that optimize both the maximal concentration and the time above a minimum threshold of concentration.
Along with pathways to accelerated approval, a large and growing unmet need, the antibacterials field has the advantage of highly predictive early studies that de-risk late stage trials. We at Spero intend to leverage this huge advantage we have in the field and show our work to the external world ahead of Phase III about dose selection. In my observation, we as a field are very transparent about how well our drugs kill bugs, but our record is more mixed about support of dose selection. Not all drugs are created equal in their ability to get to the site of infection consistently. We’d hope that the investment, pharmaceutical, and academic community demand this of us in general to ensure that the right drugs with the right PK properties at the right dose make it to Phase III and succeed. A win for our drugs is a win for the field.
About the Authors:
Chief Executive Officer of Spero Therapeutics
Chief Medical Officer of Spero Therapeutics
President of the Institute for Clinical Pharmacodynamics