Positioning Drug Candidates in a Competitive Landscape - an integrated, data-driven approach
Wenping Wang
JNJ PRD
Drug development decision making is greatly facilitated by having a model of the likely clinical profile of the new investigational drug (NCE) readily available. The model of the clinical profile should quantify the probability distribution of clinical safety, tolerability and efficacy as a function of treatment strategy (dose) and patient population attributes. Preferably the model should include competitors or treatment alternatives so that a quantitative assessment can be made of the clinical benefits and drawbacks of the NCE relative to those competitors. Building such an integrated model requires the joint analysis of data from multiple sources, different levels of detail, and potentially different endpoints. This often includes study level data from individual patients available for the NCE as well as summary data on competitors found in the literature.
For instance, for a team trying to develop a Factor Xa Inhibitor (NUXa) indicated for the prophylaxis of deep vein thrombosis, the following questions may be relevant.
- How does the efficacy of NUXa 3 mg compare to that of enoxaparin 40 mg
- How does the safety of NUXa 3 mg compare to that of enoxaparin 40 mg
- If interested in lowering DVT by 5% over enoxaparin 40 mg, what is the likely dose of NUXa?
- Is safety a concern with this dose?
- What’s the optimal registration strategy for product differentiation?
The purpose of this talk is to show an example of how such integrated modeling together with DMXTM technology was used to support key development decisions for gemcabene, an investigational new drug that lowers low-density lipoprotein cholesterol (LDL-C), decreases triglycerides and raises high-density lipoprotein cholesterol (HDL-C) (1). HMG-CoA reductase inhibitors, or statins, are the most widely used drugs to reduce LDL-C and six statins, atorvastatin, rosuvastatin, simvastatin, lovastatin, pravastatin and fluvastatin, are currently on the market. The major distinguishing feature between the statins is the magnitude by which they lower LDL-C in the available dose range. Recently ezetimibe, a chlosterol absorption inhibitor, was introduced to the market to be given in combination with statins to further reduce LDL-C and achieve the aggressive new target levels that were set by the U.S. National Cholesterol Education Program (NCEP) (2). Like ezetimibe, gemcabene was intended to be given in combination with a statin. To evaluate the product profile of gemcabene, alone and in combination with a statin, we developed a model for the lipid effects (LDL-C and HDL-C), adverse effect such as persistent ALT elevation and myalgia, and tolerability issues such as headache for five of the currently marketed statins, ezetimibe, and gemcabene and the combination of ezetimibe or gemcabene with a statin. To evaluate the impact of treatment with a combination of a statin with gemcabene or ezetimibe on coronary artery disease, a model was established to predict the risk reduction relative to placebo or compared to other statin treatments on basis of the lipid effects. Whereas all aspects of the product profile contributed to decision making, the LDL-C effect was an important deciding factor and is the main focus of this paper.