Current Topics in Medicinal Chemistry - Volume 5, Issue 11, 2005

The biopharmaceutical industry is facing challenges from increased generic competition, regulatory changes and other factors negatively impacting pharma economics. Industry is also presented with opportunities for improving overall research & development and business efficiency via de-risking development of novel drug candidates. Approaches to improve efficiency and decrease risk include in vitro and in vivo ADME (absorption, distribution, metabolism and excretion), biomarker-enabled development strategies, intelligent clinical trial design and overall risk management. ADME strategies to select and optimize drug candidates can significantly reduce PK-based failures in clinical trials, and more successfully predict drug-drug interaction potentials in the clinic. ADME strategies are reviewed in this issue by Balani et al. (Millenium Pharmaceuticals, Inc.). Biomarker approaches can facilitate transition between discovery, experimental medicine and full development and in some cases be a part of postmarketing activities. Biomarker methodologies include genomics, pharmacogenomics, proteomics, integrative strategies and molecular imaging. Pharmacogenomics and its role in discovery and development are discussed by Johnson et al. from Pfizer Global Research and Development. Integrative strategies, such as Functional Informatics, could incorporate several different technologies to cross validate findings. Genomics, proteomics and integrative strategies as they can be applied to clinical oncology biomarker discovery are reviewed by Belkowski and colleagues from the Johnson & Johnson Pharmaceutical Research and Development, L.L.C. Noninvasive techniques are generally based on imaging modalities and include light imaging, CT, MRI, PET as well as different combinations of these modalities, for example PET/CT. Although all of these technologies can facilitate preclinical and clinical activities, it is beyond this issue to cover them in detail. PET provides an opportunity to non-invasively evaluate in vivo PK, receptor occupancy and pharmacodynamics (PD), and PK/PD, and could lead to a better prediction of dosing to be used in the clinic as well as to a reduction in the cost and duration of phase II clinical trials. It could also provide information to enhance our understanding of the mechanism(s) of action. PET technology provides an ability to complement with assays of therapeutic efficacy and potential adverse events. In diseases that are difficult to approach with traditional methods, PET will accelerate and improve compound development. PET technology is reviewed in this issue by Wang and Maurer from the Alza Corporation. Selection of the right dosing is of paramount importance for informed go/no go decision in clinical development. Of equal importance is a well-conceived overall design of a clinical study. This is of particular importance to trials with high placebo response rate and Yang, Cusin, and Fava from the Depression Clinical and Research Program at the Massachusetts General Hospital discuss various strategies to address this problem in antidepressant trials. Finally, Martin Mackay and his co-authors from Pfizer talk about overall strategies (technology, organizational, etc.) to handle risk in drug discovery and development. This issue is comprised of well referenced up-to-date edited manuscripts from leaders in the pharmaceutical industry and academia.

The high-throughput screening in drug discovery for absorption, distribution, metabolism and excretion (ADME) properties has become the norm in the industry. Only a few years ago it was ADME properties that were attributed to more failure of drugs than efficacy or safety in the clinic trials. With the realization of new techniques and refinement of existing techniques better projections for the pharmacokinetic properties of compounds in humans are being made, shifting the drug failure attributes more to the safety and efficacy properties of drug candidates. There are a tremendous number of tools available to discovery scientists to screen compounds for optimization of ADME properties and selection of better candidates. However, the use of these tools has generally been to characterize these compounds rather than to select among them. This report discusses applications of the available ADME tools to better understand the clinical implication of these properties, and to optimize these properties. It also provides tracts for timing of studies with respect to the stage of the compound during discovery, by means of a discovery assay by stage (DABS) paradigm. The DABS provide the team with a rationale for the types of studies to be done during hit-to-lead, early and late lead optimization stages of discovery, as well as outlining the deliverables (objectives) at those stages. DABS has proven to be optimal for efficient utilization of resources and helped the discovery team to track the progress of compounds and projects.

To deliver on the promise of personalized medicine requires the integration of pharmacogenomics into the discovery and development of medicines. Over the last few years the pharmaceutical industry has been building considerable resources to achieve that. However, this requires new skill sets, capabilities and infrastructures which have not been a traditional part of the industry's efforts. In this article we describe how the integration of genetics and pharmacogenomics data has begun to deliver success and illustrate the challenges that the new science and technologies bring and how these challenges can be addressed in order to deliver on the promise.

Biomarkers in the clinical oncology field can have tremendous therapeutic impact especially if the marker is detected before clinical symptoms. This impact can be extended to the evaluation of clinical oncology treatments allowing evaluation of potential compounds to determine their efficacy in the disease treatment. The discovery of clinical biomarkers can consume time, resources and costs. Therefore, it is important that the most effective strategies are employed to discover these biomarkers. These strategies may include the integration of available genomic, proteomic and histopathological technologies, which could reduce the costs and aid in the validation of the biomarker. Certainly the type of biomarker needed to address a particularly defined problem will drive the type of technology. However, a single biomarker to diagnose a specific cancer can be as elusive as relying on a single technology. This review examines some of the technologies used to discover biomarkers and presents the use of combinatorial technical synergies to discover and validate potential clinical oncology biomarkers.

Positron Emission Tomography (PET) is a sophisticated nuclear imaging modality that affords researchers the ability to conduct both functional and molecular imaging on biological and biochemical processes in vivo. In functional imaging, biological parameters such as metabolic rate and perfusion that can be altered by disease or treatment are monitored. In molecular imaging, PET can be used to examine and quantify cellular events such as cell trafficking, receptor binding and gene expression. Therefore, PET is an important tool to elucidate mechanisms associated with diseases and drug actions. In addition to PET, microPET is designed to image small animals. A great tool to facilitate preclinical studies and basic research, it can eliminate the need of sacrificing the animal by enabling noninvasive, longitudinal, and serial studies. The results from preclinical studies using microPET can be directly correlated with clinical studies using PET, thus bridging the chasm that used to separate the 2 pivotal phases in drug development. This review first describes the basic principles of PET and compares it to other imaging modalities. Then, PET procedures and PET isotopes and tracers synthesis are outlined. Next, functional and molecular PET imaging applications in the fields of oncology, neurology, and cardiology in both humans and animals are presented. Spanning a wide range, these applications demonstrate the versatility of PET and how it can be used to accelerate drug discovery and development. Finally, the advantages and limitations of PET and how it can be used in the future to minimize risks of drug development are discussed.

In psychiatry, particularly in antidepressant clinical studies, placebo-controlled trials often yield results that are very difficult to interpret because of robust placebo responses. Meta-analyses of trials in major depressive disorder (MDD) suggest that drug-placebo differences in response rates range from 11% to 18%. However, in trials of marketed antidepressants present in the FDA databases, antidepressant drugs were superior to placebo in only 45 out of 93 RCTs (48%), and the placebo response overall appears to have increased over time. This gradual increase in placebo response rates may lead to delays in bringing new antidepressant treatments to the market, increased costs of antidepressant drug development and, in some cases, decisions to stop the development of certain compounds, or FDA decisions to not approve new treatments. A number of possible contributing factors to this significant placebo response in MDD have been identified, but further studies are needed. Many of the remedies used by researchers to minimize the placebo response, such as lead-in periods or shortening the duration of study visits, have failed to show consistent benefits. From our analysis of published studies, it appears that expectations about the speed of response may be shaped by the duration of the trial and that most of the placebo response occurs in the first half of the trial, regardless of its duration. These observations have led us to develop a novel approach to the placebo response problem called the Sequential Parallel Comparison Design.

The ever increasing cost of discovery and development of new pharmaceutical agents mandates that risk be managed more aggressively. Decisions that are based on data, well-understood experience, and the value of the project itself must be made sooner in the overall process. Uncontrolled risk must be addressed and managed. The reward system within pharma must treat negative decisions as productive and important. Clearly, risk must be addressed concertedly at the technical, strategic, and organizational levels. This is not an option. When we do our job well in discovery and early development, a compound's chances in the clinic, the regulatory area, and the market will all be better.