Member SpotlightsDrug Discovery Applications in Dyslipidemia and Cardiovascular Disease Scott Greenfeder, Ph.D. A Science Advisory Board Member Since 1998  Scott Greenfeder, Ph.D. Scott Greenfeder, Ph.D., is a Research Fellow for the Schering-Plough Research Institute, US. Greenfeder received his Ph.D. from the University of Medicine and Dentistry of New Jersey (1991), and completed his post-doctoral work at Hofmann La-Roche Pharmaceuticals (1992-1995). He joined the Schering-Plough Research Institute (SPRI) in 1995, where he currently conducts research on identification of new drug candidates and targets in dyslipidemia and cardiovascular disease. Greenfeder is currently a member of the American Association for the Advancement of Science (AAAS) and the Endocrinology Society. In his leisure time, Greenfeder enjoys running and photography. Academic and Professional Background. I graduated from Rutgers College, New Jersey, with a BA in Microbiology in 1984. I received my Ph.D. from the University of Medicine and Dentistry of New Jersey in 1991. My thesis work focused on the analysis of DNA replication fork movement on a circular chromosome of the yeast Saccharomyces cerevisiae. I then completed a post-doctoral assignment at Hofmann La-Roche Pharmaceuticals in Nutley, NJ from 1992-1995. During my post-doc, I identified a second sub-unit of the Interleukin-1 Receptor, which is responsible for full signal transduction by the receptor complex. In 1995 I joined the Allergy Department of the Schering-Plough Research Institute (SPRI) as a Senior Scientist, and in 2003 I joined the Cardiovascular and Metabolic Disease Department where I'm currently a Research Fellow. Research Interests My current research is focused on the development of new drugs and identification of new targets in the area of dyslipidemia and cardiovascular disease. My lab’s role is in the early in-vitro stage of drug discovery. We identify and validate new drug targets, establish screening assays for those targets and, if warranted, conduct screening in concert with our medicinal chemistry colleagues for lead optimization. I am also involved on several teams ranging from Preclinical Target teams to Clinical Development teams. As an undergraduate I was interested in medicine. A brief stint as a volunteer in the OR of a local hospital convinced me that research was more my path. My graduate work was centered around elucidation of DNA replication fork movement in yeast. While this was an interesting project and I learned a tremendous amount about yeast, DNA replication and more importantly about conducting good solid science, I realized that my interests were toward research that could more directly impact human disease. After some searching I decided that the best place for me to have such an impact was in the pharmaceutical industry in the pursuit of new medicines. Future Endeavors I am pleased to say that I am right where I expected to be in terms of my career. I have been lucky to have the opportunity to work with talented, bright and affable colleagues. I have been able to strike a balance between strict drug discovery and basic science, which has resulted in both advancement of clinical drug candidates and scientific publications. I would like to continue to support drug discovery efforts in my current position and continue to grow in management responsibility. Ultimately to see one of the drugs that we have identified reach the marketplace and have a positive impact on the health of patients would be a very proud achievement. The following questions are specific to our current Spotlight on Drug Discovery: In what way does your position contribute to the drug discovery pipeline? The work in my lab ranges from research focused on discovery of new targets for drug intervention to support of ongoing compound lead optimization programs and clinical development programs. We are primarily a group with expertise in in-vitro techniques although we have recently begun to utilize in-vivo approaches to further our target discovery efforts. We are currently involved in two programs at very different stages. One is very early. We identified this particular target through the scientific literature. We have established methods to assay the function of this target to facilitate the identification of compounds that modulate that function. We are currently working with colleagues in our high-throughput screening group to miniaturize our method. Small-scale compound screening in our lab has identified a few promising “hits” which we are pursuing. We are hopeful that we may be able to begin a lead optimization program for this target in the near future. The second program we are involved in is at a much later stage. In this program we have completed the lead optimization efforts and are now in the Clinical Development phase heading toward “First In Human” testing. It is very exciting and gratifying to see a compound that you worked closely with get to this stage. I am a member of the team that is moving the compound forward to the clinic and my lab continues to support these efforts when needed. What is at once fascinating and also daunting is the overall complexity of the processes required to develop a drug candidate once it has left the preclinical arena. There is a necessary interplay between a number of disciplines (chemical development, toxicology, clinical, regulatory affairs) that requires continual oversight, leadership and above all great teamwork. In addition, we have other efforts centered around the discovery and validation of new targets. In general these are experiments that utilize various forms of gene expression analyses to identify genes and gene products that may be involved in disease states or that may be part of the mechanism by which other drugs function. Are your drug discovery efforts physiology-based, target-based, or do they utilize a two-pronged approach? (At which point is your drug target identified?) Our drug discovery efforts are generally target-based. With the advances in molecular biology techniques over the past decades it has become possible to approach drug discovery in a very specific manner, looking for compounds that modulate a metabolic or signaling process at a very specific level. Therefore, our drug targets are selected prior to the identification of compounds. It will be interesting to monitor these efforts in the future. Traditionally, drugs were screened in in-vivo animal models with the readout being a physiological effect. These are low-throughput assays that can not possibly keep pace with the number of available chemical entities. The pendulum has swung to the other side with target-specific screening in very high-throughput approaches. New approaches are always being developed and hold the opportunity for a middle ground in which high-throughput cell-based physiological assays could be used that are more reflective of the in-vivo state. This would facilitate a shift back to the paradigm that the target identification process be carried out after identification of lead compounds. What disease mechanisms are particular to the drug candidate compounds that you work with? The compounds that my lab currently works on are targeted toward cardiovascular diseases. More specifically we are interested in dyslipidemia; both lowering of low density lipoprotein-cholesterol (LDL) and increasing high density lipoprotein-cholesterol (HDL-C). After initial discovery, what methods are used to validate the target before assay development? Target validation can take a number of avenues depending on the type of target and the availability of tools. At the base, expression profiling is important. Knowledge of the cells/tissues in which the target is expressed is a first step in validation of a particular target. Not only does this information inform us if we will be targeting the appropriate tissue etc., it often gives us clues as to potential side effect liabilities we may encounter or at least consider as we progress. The further validation is again dependent on what tools are available for the target. In the “best case” scenario we have an agent (small molecule or antibody) that can be employed to test the effect of modulating the target in either relevant cell or in-vivo models of the particular disease. If a tool is not available other methods are used. Traditionally knock-out and/or transgenic mouse strains have been used to validate targets. More recently RNAi has come into play as a method to modulate a protein of interest. RNAi has been used in cell culture experiments to inhibit the target protein and reveal its role in a given signaling pathway. In-vivo RNAi also holds promise as an alternative method for inhibition of a target protein in animal models. What technology or knowledge limitations can contribute to the high failure rate of compound screening? I don’t think I would characterize the failure rate of compound screening as “high”. There are certainly times when a screening campaign yields no useful lead compounds but this by no means is the rule. Generally this occurs if the screening technology is not quite the right one for the given target. In addition, the nature of the target itself can contribute significantly to failures in screening. As an example, it has been traditionally much more difficult to find potent inhibitors of large protein:protein interactions than of enzymes. Lack of knowledge about the specifics of a target can also lead to problems in screening. This sometimes manifests as a large number of false positives. The nature of the compound library that is screened also has a major impact on success. Broader, more diverse collections will yield a higher likelihood of success at a number of diverse targets. Targeted libraries or those that are historically slanted toward certain target classes may yield higher potency leads for those targets. Beyond initial screening, compounds fail for a number of reasons. In the preclinical arena compounds often fail due to drug safety or pharmacokinetic issues such as overt toxicology or undesirable metabolic profiles. Once in the clinic compound failure generally occurs due to toxicity or side effect or lack of clinical efficacy. The clinical failure of a drug points up our current inability to predict with certainty the behavior of a drug in man. How will increased efficiencies in genomics technologies contribute to the progress of drug discovery? In the short term, increased efficiencies in genomics technologies will aid the target identification and validation aspects of drug discovery. Increased knowledge of gene expression patterns and the ability to carry out gene expression profiling in animal models of disease will be helpful. Additionally, the ability to cross-reference findings from these models to gene expression analyses from human disease tissues will have great value. The more data available to relate findings in preclinical models to actual human disease states, the better decisions can be made regarding specific drug targets. The increasing technology surrounding RNAi and shRNA capabilities will also have impact. The ability to now create mouse strains with inducible RNAi presents the opportunity to achieve a pharmacologic-type inhibition of a protein without a small molecule or antibody tool. This technology eliminates the issue of compensation from other genes which often confounds knock-out mouse studies. In addition, the nature of the inducible RNAi is such that different levels of inhibition can be achieved by varying levels of the inducer. Genomics technologies will also impact the development of biomarkers for given diseases and targets. The ability to assess both the activity and efficacy of a given drug candidate using biomarkers is becoming a more important aspect of advancing that candidate in the clinical arena. Relevant biomarkers allow faster decision making about the value of a drug candidate. In the longer term, greater mutational analyses of human genes (e.g. in the form of SNP analysis) will allow us to determine if a significant percentage of patients will have different responses to a drug than is expected. We may eventually see that, for some drugs, there could be two or more entities for a target each that acts at a different version of the target. This is truly a step toward “personalized medicine”. Do you believe there has been a recent demand for quality over quantity of drug candidate compounds? What short or long-term effects will a demand for a higher compound success rate have on drug discovery companies? I believe that the current demand is for a larger quantity of higher quality drug candidates. These philosophies are not mutually exclusive. At the end of the day it is about facilitating better decision making and about having more “shots on goal”. Higher quality stems from a number of areas in the drug discovery process. It first starts with high quality decision making in the target identification and validation arena. As I suggested above, the increased genomics technology available may allow for decisions on targets to be more meaningful. For example, the knowledge that a particular gene polymorphism is associated with a human disease is strong indication of an important target, or the ability to associate a change in a particular preclinical model with changes in human disease yields higher confidence in the validity of a given target. Quality is also influenced by compound screening and also by the compound library that is screened. Larger diverse chemical libraries generally contribute to multiple lead compound structures. The ability to pursue multiple structural classes of compounds in parallel allows for better decision making about the final clinical candidate. Secondary analyses of drug candidates are also very important in determining quality. Preclinical drug safety and toxicology analyses reveal potential issues which may arise in the clinical setting. High quality systems to assess these aspects of drug candidates facilitate the progression of candidates with a higher likelihood of success. Continued advances in technology surrounding all aspects of drug discovery will allow higher quality decision making on more drug candidates. This is one of the reasons why the call for more high quality candidates is feasible. In the long-term these demands will result in an increased number of effective medicines for patients. In addition, we will likely see medicines for more diseases as our understanding of various disease pathophysiologies increases and our ability to choose high potential targets for those diseases evolves. In the short-term these demands create a sense of excitement and opportunity but at the same time, create some degree of stress and uncertainty. In many arenas current demand may outpace resources. It will take some time for new technologies to be brought to bear on these issues and to more efficiently utilize resources to make better and faster decisions. To discuss Drug Discovery and other topics with fellow Science Advisory Board members, please visit our community forum. The following are publications authored and co-authored by Greenfeder that are relevant to this Member Spotlight: Smith Torhan, A, B. Cheewatrakoolpong, L. Kwee, S. Greenfeder 2007, Cloning and characterization of the hamster and guinea pig nicotinic acid receptors. J. Lipid Res. 48:2065. Cheewatrakoolpong, B., H. Gilchrest, J.C. Anthes, S. Greenfeder, 2005. Identification and characterization of splice variants of the human P2X7 ATP channel. Biochem Biophys Res Commun, 332:17. Gilchrest, H., B. Cheewatrokoolpong, M. Billah, R.W. Egan, J.C. Anthes, S. Greenfeder. 2003. Human cord blood-derived mast cells synthesize and release I-309 in response to IgE. Life Sciences 73:2571. Greenfeder, S., H. Gilchrest, B. Cheewatrakoolpong, S. Eckel, M. Billah, R.W. Egan, J.C. Anthes. 2003. Development of a real-time tryptase release assay from human umbilical cord blood-derived mast cells. Biotechnique 34:910. Greenfeder, S., J.C. Anthes. 2002. New asthma targets: Recent clinical and preclinical advances. Curr. Opin. Chem. Biol. 6:526. Greenfeder, S. S.P. Umland, F.M. Cuss, R.W. Chapman, R.W. Egan. 2001. Th2 cytokines in asthma. The role of interleukin-5 in allergic eosinophilic disease. Resp. Rev. 2:71. Greenfeder, S., B. Cheewatrakoolpong, J. Anthes, M. Billah, R.W. Egan, J.E. Brown and N. Murgolo. 1997. Two related neurokinin-1 receptor antagonists have overlapping but different binding sites. Bioorg. Med. Chem. 6:189. Greenfeder, S.A., P. Nunes, L. Kwee, M. Labow, R.A. Chizzonite and G. Ju. 1995. Molecular cloning and characterization of a second subunit of the murine Interleukin 1 receptor complex. J. Biol. Chem. 270:13757. Greenfeder, S.A., T. Varnell, K. Lombard-Gilooly, D. Shuster, D. Ryan, W. Levin, K. McIntyre, G. Powers and G. Ju. 1995. Insertion of a structural domain of Interleukin (IL)-1β confers agonist activity to the IL-1 receptor antagonist. J. Biol. Chem. 270:22460. Greenfeder, S.A. and C.S. Newlon. 1992. Replication forks pause at yeast centromeres. Mol. Cell. Biol. 12:4056. Greenfeder, S.A. and C.S. Newlon. 1992. A replication map of a 61-kb circular derivative of Saccharomyces cerevisiae chromosome III. Mol. Biol. Cell 3:999. ### << Previous Next >> [ View All Member Spotlights ] |
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