Personalised Medicine
Further development with a redesigned Phase II endpoint in selected patients may not meet the marketing criteria and incur tremendous addition- al cost, as the programme is set back by about two years while the biomarker development and repeat studies take place.
Figure 2
Graphic illustration of the impact of subpopulation
responses on overall study outcome in a Phase II trial of an investigational drug for diabetes. Without
segmentation of the patient population prior to the
conduct of the trial, the robust response of the smaller subpopulation is diluted by the lackluster response in 70% of the trial participants. Y-axis indicates magnitude of decline in plasma glucose concentrations
clinically and commercially desired goal for the outcome of the study is a drop in 24-hour mean glucose by 40mg/dL. However, the overall drop is ~28mg/dL and the trial is deemed a failure, ie the mechanism does not have the necessary efficacy to be useful and marketable. Additional post hoc analysis of the data suggests that there are two populations of responses: one in which the mean decline in 24-hour glucose is 80mg/dL, represent- ing 30% of the study population, and a second group of the remaining 70% which yielded a mean decrease of 5mg/dL. It is clear from the analysis that the robust response of 80mg/dL was diluted by the tepid response in the larger group. At this point, however, the team is challenged wondering if the upper 30% was truly distinct from the remainder. Or perhaps it was simply the nature of statistical distributions and the observed 30% occurred by chance. Assuming that there were no obvious pharmacokinetic differences between the groups, the project team will likely be unable to separate responders from non-respon- ders and the project ends short of the conduct of another trial, even a limited one. Even if the team manages to identify potential stratification bio- markers, it is very difficult to retrofit a patient sub- population analysis on a completed trial. First, if there is separation from the post hoc analysis, then another prospective trial would be necessary to achieve proof-of-concept (POC). This inefficient process would be shunned by most given limited resources and the prevailing doubt of resurrecting a failed drug. Second, the trial was designed to fit a product profile/marketing plan that contains spe- cific assumptions for population size and efficacy.
50
There are current examples available that illus- trate this point, largely advanced in oncology. Consider first the example of KRAS mutations and EGF receptor (EGFR) inhibition. It has been clear- ly demonstrated that KRAS mutations abrogate the positive effects of agents such as panitumum- ab20-21. In these studies, subjects with metastatic colon cancer and KRAS mutations and who received panitumumab fared no better than those treated with standard therapy. In subjects with wild type KRAS, a demonstrable effect on progres- sion-free survival due to panitumumab was observ- able20-21. Imagine, however, that the first trial(s) with panitumumab or other EGFR antagonists unknowingly included many subjects with the mutation. The false negative conclusion from those studies could have been that panitumumab (or other EGFR antagonists) was not effective. Similarly, Her2 overexpression is the critical factor determining the responsiveness of patients with breast cancer to trastuzumab. As Her2 overexpres- sion is present in only ~20% of patients with breast cancer, it is easy to project that, without pre- planning, a trial of women with breast cancer and no stratification would have likely yielded a nega- tive result22 (Figure 3). Moreover, given the car- diotoxicity associated with trastuzumab23, with- out patient stratification there would have been many more adverse effects without its benefit. It is the premise of the authors that, beyond oncology, there are likely many of these subsets of patients who suffer from apparently similar clinical disease, but whose molecular underpinnings are likely different. Similar ideas have been expressed for rheumatoid arthritis24, ulcerative colitis25 as well as diabetes26. If this is true, then trying to cre- ate molecularly-refined therapeutics without defin- ing the appropriate patient populations markedly inflates the probability of failure. The industry will likely continue to have productivity problems from Phase II failures until this incongruence is ade- quately addressed. The only other alternative is that new agents are produced against targets that are proximal in a pathway or have key regulatory or broad-spectrum functions, such as those used in oncology or anti-inflammatory agents that are broadly immunosuppressive. The problem with these targets is that they will likely have more adverse effects associated with their use.
Drug Discovery World Summer 2011
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