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    • Managing Drug Development Challenges for Inflammation Therapies

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      Published On Nov 30 2012, 2:39 AM

      InflammationIncorporating technologies such as biomarkers into the development of inflammation therapies can improve the development and delivery of the right therapy, at the right dose, to the right patient. Nonetheless, there are numerous risk factors inherent in inflammation studies and drug development overall. It's crucial to identify these risks early on in your development plan and develop mitigation strategies that will help decrease your chances for failure.

      Inflammation: A Target with Vast Potential

      Inflammation plays a pivotal role in disease, providing multiple new targets for anti-inflammatory therapy. Traditionally, inflammatory diseases were addressed in a piecemeal fashion, dictated by the physical site of the disease (e.g. lungs, guts, joints, etc.) However, recent discovery that seemingly unrelated diseases, like arthritis and IBD, can respond to the same biological therapies has led to the treatment of a newly conceived group of diseases called Immune-Mediated Inflammatory Disorders (IMIDs). More than a name and classification, IMIDs represent a significant shift in the approach to the management of traditional inflammatory diseases from organ-based symptom relief to mechanism-based treatment. Utilizing anti-cytokine as a strategy of targeted, active immunotherapy has been effective in treating multiple inflammatory conditions, confirming the IMID paradigm.

      Biomarkers: Driving IMID Opportunities

      Biomarkers are being leveraged to support rational, expedited IMID drug development. Currently, inflammation biomarkers are being used to 1) increase the ability to detect early therapeutic effects with novel agents 2) allow expedited human proof of mechanism/concept studies to screen out and fast track promising drug candidates 3) identify subgroups that may benefit from more (or less) intensive immunosuppressive therapy or use of novel therapy and 4) predict subject response to treatment allowing closer monitoring of individuals judged to be most at risk of relapse.

      Biomarkers can be categorized into four different types. Target biomarkers demonstrate drug interaction with targets, such as receptor occupancy, using a positron emission tomography (PET) ligand. Mechanism biomarkers demonstrate physiological, biochemical, genomic, or behavioral changes downstream of the drug target. Outcome biomarkers act as surrogates for clinical efficacy or safety and are independent of drug mechanism. Finally, toxicity biomarkers can be useful to identify a safe dose for administration.

      This leads to two important principles. First, patients with the same disease phenotype do not all have the same level of abnormal activity of a biochemical pathway or expression of a drug target. The second principle is that a drug targeting abnormality will be more effective in patients with the most abnormal expression of that pathway. The following rheumatoid arthritis (RA) study helps explain this second principle.

      Rheumatoid Arthritis Study with Infliximab Leads to Interesting Hypothesis

      There are approximately nineteen genes that are significantly associated with RA susceptibility, severity, or response to therapy and have been associated with differences in T-lymphocyte activation, macrophage function, specific cytokine, and inflammatory signaling pathways and/or inflammatory pathway dysregulation. In general, rheumatologists treat patients without considering these individual differences and instead they use a "try it and see" paradigm.

      TNF-alpha production is influenced by SNPs in the promoter region of the gene, which can lead to mutations. In-vitro cells from subjects with A/A and A/G genotypes produce significantly more TNF-alpha in response to inflammatory stimuli when tested in in-vitro cells. A small study looked at this and found that patients with the G/G genoptype had about an 81% improvement in response to the drug Infliximab, whereas patients with the A/A or A/G genotype had about a 42% improvement.

      This leads to an interesting hypothesis that genetic variation data might be used to design a stratified, early Proof-of-Concept (POC) clinical trial. The data could also be used to develop a drug/diagnostic combination that allows for personalized dosing that reduces infectious, adverse events and improves efficacy. In this particular case, patients with the G/G genotype would receive less TNF-alpha inhibition, whereas patients with the A/A or A/G genotype would receive more TNF-alpha inhibition.

      Identifying Drug Development Risk Factors

      There are several red flags or risk factors to be aware of during drug development. Anything from an unprecedented target, to an unusual dose response, to a high efficacy target, to unusual dose response curves, plus many other factors, can increase your risk of failure. Overall, it's important to identify how much risk is in the target for the indication in mind. You can identify the potential risk through some of the following ways.

      First, determine if there is precedence for the drug target. Literature on efficacy of the mechanism, even if the product has failed, can be useful, plus a successful biological drug can validate a target for a small molecule drug. Second, a human genetic variation can validate a target. Another way to identify risk is to determine if the target in a pathway is known to disease expression. Finally, establish whether the target expression is limited to disease tissue. If it is limited, it will likely be better tolerated. However, if the target expression is more widely spread out, you may see more problems as you are going through development.

      It's critical to be aware of molecules with multiple high risk factors and plan accordingly. During your development plan, develop mitigation strategies that will help you decrease your risk of failure.

      Visit here for more information on achieving proof-of-concept data for inflammation drug studies.

      Eric Lang, M.D., joined Covance in February 2012 as Vice President, Molecule Development Group. Dr. Lang is a Board Certified Anesthesiologist and pain management specialist by training. He has 15 years of pharmaceutical industry experience in large and small pharma. Prior to joining Covance, Dr. Lang held leadership roles in Clinical Development at Grunenthal USA, Javelin Pharmaceuticals, Novartis Consumer Health and Johnson & Johnson. Dr. Lang's overall experience has included early and later stage clinical development, regulatory, and medico-marketing strategy, preparation of clinical development and risk management plans, due diligence and target product profile development. Dr. Lang received his Bachelor of Medicine degree and MD from the Ben Gurion University of the Negev in Israel and completed several fellowships at Emory University in Atlanta, GA. Dr. Lang has been published in over 25 peer reviewed articles, chapters and scientific abstracts.

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