DOCSLIB.ORG

Intelligent Drug Discovery Powered by AI About the Deloitte Centre for Health Solutions

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Intelligent Drug Discovery Powered by AI About the Deloitte Centre for Health Solutions A report from the Deloitte Centre for Health Solutions Intelligent drug discovery Powered by AI About the Deloitte Centre for Health Solutions The Deloitte Centre for Health Solutions (CfHS) is the research arm of Deloitte’s Life Sciences and Health Care practices. We combine creative thinking, robust research and our industry experience to develop evidence-based perspectives on some of the biggest and most challenging issues to help our clients to transform themselves and, importantly, benefit the patient. At a pivotal and challenging time for the industry, we use our research to encourage collaboration across all stakeholders, from pharmaceuticals and medical innovation, health care management and reform, to the patient and health care consumer. Connect To learn more about the CfHS and our research, please visit www.deloitte.co.uk/centreforhealthsolutions Subscribe To receive upcoming thought leadership publications, events and blogs from the UK Centre, please visit https://www.deloitte.co.uk/aem/centre-for-health-solutions.cfm To subscribe to our blog, please visit https://blogs.deloitte.co.uk/health/ Life sciences companies continue to respond to a changing global landscape, and strive to pursue innovative solutions to address today’s challenges. Deloitte understands the complexity of these challenges, and works with clients worldwide to drive progress and bring discoveries to life. Contents Accelerating drug discovery 2 The rise of AI drug discovery disruptors 8 Key considerations for biopharma’s adoption of AI 18 The future of drug discovery: Delivering ‘4P’ medicine 25 Endnotes 30 Intelligent drug discovery Accelerating drug discovery The Deloitte Intelligent biopharma series explores how artificial intelligence (AI) technologies will affect each step of the biopharma value chain.1 This report, the second in our series, examines how AI is helping to accelerate the efficiency and cost-effectiveness of drug discovery. RUG DISCOVERY IS the first step of the manufacturing and administration routes, low value chain that identifies new candidate specificity and a stable shelf life, meaning they are therapeutics for treating or curing human safe and effective for large groups of people. D 2 diseases. It is the initial stage of biopharma However, low specificity can also lead to side effects, research and development (R&D) and involves the reducing the chances of success in clinical trials. identification and optimisation of potential new drugs and a preclinical in vivo validation through Since the 1990s, scientific and technological cell assays and animal models. Successful candi- advances have led to the discovery of larger, more dates that meet the regulatory requirements applied complex, biological therapeutics known as biologics. to drug discovery move into the clinical trial phase, In contrast to chemically synthesised small mole- where they are tested for efficacy and safety in cules, biologics are produced or isolated from living humans.3 Our next report in the series examines organisms and include a wide range of products the impact AI is having on clinical trials (Intelligent such as allergenics, antisense drugs, blood and clinical trials: Transforming through engagement). blood components, recombinant therapeutic DNA and proteins, and vaccines. The evolution of drug discovery Biologics are highly specific to their target and have invoked high levels of media and investor interest Historically, the discovery of new therapeutics due to their innovative techniques and potential to involved the extraction of ingredients from natural cure previously untreatable diseases. Only 17 of the products and basic research to find potential treat- 59 drugs approved by Food and Drug Administration ments. Progress was generally slow, frustrating and (FDA) in 2018 were biologics, largely due to the com- labour intensive. In some cases, discoveries plex manufacturing and administration routes.5 As occurred due to unexpected events and observa- most pharma companies have integrated biologics tions (such as penicillin). The majority of drugs into their pipelines, for the purpose of this report we discovered during the 20th century were chemically refer to all pharma companies as biopharma compa- synthesised small molecules, which still make up 90 nies. Figure 1 provides a timeline on the history and per cent of drugs on the market today.4 The advan- progression of drug discovery paradigms. tages of small molecules include simple 2 Powered by AI FIGURE 1 The history and progression of drug discovery paradigms Main research discoveries Drug approvals Main technological advances Main awards and prizes DNA crystals imaged Double-helical DNA Inactivated polio Interferon, a naturally using X-ray diffraction, structure discovered vaccine introduced occurring anti-viral paving the way to protein discovered discover DNA structure 1952 1953 1955 1957 Ibuprofen approved First production of Protein Data Bank providing First measles Development of by the FDA recombinant DNA X-ray crystal structures of vaccine licensed Solid-Phase Peptide proteins used for structure Synthesis (SPPS) based drug design 1974 1972 1971 1963 First production First nonmathematical Introduction of FDA approval for Polymerase chain of monoclonal method for rational Computer-Aided recombinant reaction (PCR) antibodies drug design Drug Design human insulin, invented, allowing (CADD) Humulin large scale applications of recombinant DNA 1975 1977 1981 1982 1983 Human Genome Project First statin for Introduction of Nobel Prize in Chemistry awarded for initiated human use combinatorial chemistry work on SPPS (Lovastatin) and phage display First miniaturised device for approved by technique Nobel Prize in Physiology and Medicine awarded chemical analysis the FDA for work on monoclonal antibodies production 1990 1987 1985 1984 The first microchip/ microarray The first example of a Nobel Prize in Chemistry The FDA approved interferon company founded (Affymetrix) small-molecule combinatorial awarded the invention for adjuvant therapy of library reported of the PCR method melanoma patients 1991 1992 1993 1995 CRISPR invented as a EMA approved Human genome sequencing The FDA approved The first drug based on gene editing tool in the use of gene completed, which allowed for Humira, the world’s a monoclonal antibody mammalian cells therapy product the development of emerging bestselling drug (Rituximab) approved (Glybera) pharmacogenomics for medical use technologies 2013 2012 2003 2002 1997 The FDA approved the Nobel Prize in Chemistry The FDA approved the AI-enabled technology for de novo design of use of a cell-based awarded for work on use of a CRISPR-based small-molecules (GENTRL) by Insilico Medicine gene therapy product phage display of peptides therapy to treat a rare delivered a lead compound against fibrosis in (Kymriah) and antibodies genetic ocular disorder 46 days rather than years 2017 2018 2019 Source: Deloitte research supported by Deep Knowledge Analytics. 3 Deloitte Insights | deloitte.com/insights Intelligent drug discovery Despite advances in genomics, chemical synthesis massive improvements in computing power, and other molecular biology techniques, only advances in robotics and biological techniques, and around one-third of the estimated 20,000-30,000 improved methodologies in synthetic chemistry.10 known diseases have an adequate treatment.6 7 Moreover, research published in 2017 found that the FDA had approved 1,578 drugs in total, target- The four main stages of ing only 819 disease related molecular targets out of 20,000-25,000 genes composing the human drug discovery generally genome.8,9 take fi ve to six years to complete. Discovering drugs is a crucial fi rst step in the biopharma value chain Drug discovery generally comprises four main stages (see fi gure 2). These stages take fi ve to six years to com- For the past 50 years, drug discovery has focussed plete, excluding the initial drug target identifi cation and largely on high-throughput screening for known assay development steps, which are largely driven by disease-associated targets with progress driven by academic and other research centres.11 FIGURE 2 The biopharma value chain for drug discovery Postmarket Research & Clinical Manufacturing Launch & surveillance & discovery development & supply chain commercialisation patient support STAGE 1 STAGE 2 STAGE 3 STAGE 4 First screening and Hit to lead selection Lead optimisation Preclinical testing hit identification Hits are confirmed and (drug candidate In vivo assays are performed High-throughput screening analogue clusters are selection) to test pharmacodynamics, of large libraries of synthetized three to six Lead molecules are further pharmacokinetics and chemicals to test their ability molecule clusters with modified and improved a toxicity of novel candidates to modify the target positive better affinity and drug number of drug candidates 1 in 25 drug candidates that hits are selected for further properties are selected are selected (1 in 5000 from enter preclinical phase are validation initial screening) selected for clinical trial studies The drug discovery process usually takes five to six years from the start of stage I to the end of preclinical testing. Of 10,000 small molecules initially screened, 10 are selected for clinical trials.12 Source: Deloitte analysis. Deloitte Insights | deloitte.com/insights 4 Powered by AI Drug discovery is a long, Around one-third of the above cost is spent on the expensive and often drug discovery phase.16 As shown in fi
Load more

Recommended publications
  • 1 Drug Development Working Group Report: Analysis of Existing
    Drug Development Working Group Report: Analysis of Existing Strengths, Critical Gaps, and Opportunities for Collaboration May 2014 1. Analysis. Biopharma - Focused on innovation with clinical application. Universities will play an increasingly large role in driving innovation in the biomedical industry for the foreseeable future. In New Jersey, there are several major biopharmaceutical and >350 smaller biotechnology and related companies with one or more employees. The recent integration of Rutgers creates a unique opportunity to align the University’s considerable drug discovery and development strengths. A directed effort of this sort would greatly enhance the capabilities of the University and enable University research to synergize with the biopharma industry, broadly defined. Although there have been shifts, mergers, and acquisitions in the New Jersey biopharma industry, the biopharma industry has continued to thrive. In 2003, the NY/NJ biopharma region had 17 companies with valuation >$100 M; in 2013 this region had still had 16 such companies. Moreover, the region is still vibrant: it continues to be home to large biomedical corporations, startups, entrepreneurs, and the world center for finance and capital. New Jersey also has quality industrial laboratory space, an ecosystem populated by a talented and experienced work force that has made New Jersey the “medicine chest of the world,” and an unparalleled opportunity to combine these factors in biopharma ventures that build on partnerships between Rutgers University and industry. Indeed, the primary difference between now and 15 years ago is that the present industry now is willing to reach out in a highly dynamic fashion. Rutgers is uniquely positioned to step forward as the premier university leader in biomedical innovation and development in the region.
    [Show full text]
  • Drug Design Project Tips
    Drug Design Project Information and Tips CHEM 162B (2012) Part of your grade in Drug Design courses will come from a development of a “Drug Design Project”. Students who have taken Chem162A will be able to continue their project development; students who have not taken Chem 162A can pick one of the projects developed in past and take it further. Students will present their projects during the annual Drug Design Poster Event. Students taking Chem 162 during the Winter 2011 will be able accomplish three important milestones toward completing the Project. Part of your grade will be based on your success in completing these milestones. The milestones that you are expected to complete during the Spring 2012 are: 1) Characterize a validated protein/nucleic acid target for the disease that you are working on. If the target is an enzyme, describe in detail the reaction it catalyzes. If the target is not an enzyme, describe in detail its physiological role and mode of operation 2) Obtain or create a virtual library of possible drug candidates that are expected to bind to this target and carry out virtual screening to identify best binders 3) Describe adsorption, distribution, metabolism, excretion, and possible toxicity aspects of your drug candidate(s). If appropriate, propose modifications to improve your drug. You are expected to turn in your work on each milestone by the due dates specified; you’ll automatically receive 3 points per each milestone if you submit a significantly developed work by the due date. You will earn extra 5 points if you submit all milestones by the due date.
    [Show full text]
  • Computational Approaches for Drug Design and Discovery: an Overview
    Review Article Computational Approaches for Drug Design and Discovery: An Overview Baldi A College of Pharmacy, Dr. Shri R.M.S. Institute of Science & Technology, Bhanpura, Dist. Mandsaur (M.P.), India ARTICLE INFO ABSTRACT Article history: The process of drug discovery is very complex and requires an interdisciplinary effort to design Received 12 July 2009 effective and commercially feasible drugs. The objective of drug design is to find a chemical Accepted 21 July 2009 compound that can fit to a specific cavity on a protein target both geometrically and chemically. Available online 04 February 2010 After passing the animal tests and human clinical trials, this compound becomes a drug available Keywords: to patients. The conventional drug design methods include random screening of chemicals Computer-aided drug design found in nature or synthesized in laboratories. The problems with this method are long design Combinatorial chemistry cycle and high cost. Modern approach including structure-based drug design with the help Drug of informatic technologies and computational methods has speeded up the drug discovery Structure-based drug deign process in an efficient manner. Remarkable progress has been made during the past five years in almost all the areas concerned with drug design and discovery. An improved generation of softwares with easy operation and superior computational tools to generate chemically stable and worthy compounds with refinement capability has been developed. These tools can tap into cheminformation to shorten the cycle of drug discovery, and thus make drug discovery more cost-effective. A complete overview of drug discovery process with comparison of conventional approaches of drug discovery is discussed here.
    [Show full text]
  • Opportunities and Challenges in Phenotypic Drug Discovery: an Industry Perspective
    PERSPECTIVES Nevertheless, there are still challenges in OPINION prospectively understanding the key success factors for modern PDD and how maximal Opportunities and challenges in value can be obtained. Articles published after the analysis by Swinney and Anthony have re-examined the contribution of PDD phenotypic drug discovery: an to new drug discovery6,7 and have refined the conditions for its successful application8. industry perspective Importantly, it is apparent on closer examination that the classification of drugs John G. Moffat, Fabien Vincent, Jonathan A. Lee, Jörg Eder and as ‘phenotypically discovered’ is somewhat Marco Prunotto inconsistent6,7 and that, in fact, the majority of successful drug discovery programmes Abstract | Phenotypic drug discovery (PDD) approaches do not rely on knowledge combine target knowledge and functional of the identity of a specific drug target or a hypothesis about its role in disease, in cellular assays to identify drug candidates contrast to the target-based strategies that have been widely used in the with the most advantageous molecular pharmaceutical industry in the past three decades. However, in recent years, there mechanism of action (MoA). Although there is clear evidence that phenotypic has been a resurgence in interest in PDD approaches based on their potential to screening can be an attractive proposition address the incompletely understood complexity of diseases and their promise for efficiently identifying functionally of delivering first-in-class drugs, as well as major advances in the tools for active hits that lead to first-in-class drugs, cell-based phenotypic screening. Nevertheless, PDD approaches also have the gap between a screening hit and an considerable challenges, such as hit validation and target deconvolution.
    [Show full text]
  • Medicinal Chemistry for Drug Discovery | Charles River
    Summary Medicinal chemistry is an integral part of bringing a drug through development. Our medicinal chemistry approach enables clients to benefit from efficient navigation of the early drug discovery process through to delivery of preclinical candidates. DISCOVERY Click to learn more Medicinal Chemistry for Drug Discovery Medicinal Chemistry A Proven Track Record in Drug Discovery Services: Our medicinal chemistry team has experience in progressing small molecule drug discovery programs across a broad range • Target identification of therapeutic areas and gene families. Our scientists are skilled in the design and synthesis of novel pharmacologically active - Capture Compound® mass compounds and understand the challenges facing modern drug discovery. Together, they are cited as inventors on over spectrometry (CCMS) 350 patents and have identified 80 preclinical candidates for client organizations across a variety of therapeutic areas. As • Hit-finding strategies project leaders, our chemists are fundamental in driving the program strategy and have consistently empowered our clients’ - Optimizing high-throughput success. A high proportion of candidates regularly progress to the clinic, and our first co-invented drug, Belinostat, received screening (HTS) hits marketing approval in 2015. As an organization, Charles River has worked on 85% of the therapies approved in 2018. • Hit-to-lead We have a deep understanding of the factors that drive medicinal chemistry design: structure-activity relationship (SAR), • Lead optimization biology, physical chemistry, drug metabolism and pharmacokinetics (DMPK), pharmacokinetic/pharmacodynamic (PK/PD) • Patent strategy modelling, and in vivo efficacy. Charles River scientists are skilled in structure-based and ligand-based design approaches • Preparation for IND filing utilizing our in-house computer-aided drug design (CADD) expertise.
    [Show full text]
  • Recent Advances in Automated Protein Design and Its Future
    EXPERT OPINION ON DRUG DISCOVERY 2018, VOL. 13, NO. 7, 587–604 https://doi.org/10.1080/17460441.2018.1465922 REVIEW Recent advances in automated protein design and its future challenges Dani Setiawana, Jeffrey Brenderb and Yang Zhanga,c aDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; bRadiation Biology Branch, Center for Cancer Research, National Cancer Institute – NIH, Bethesda, MD, USA; cDepartment of Biological Chemistry, University of Michigan, Ann Arbor, MI, USA ABSTRACT ARTICLE HISTORY Introduction: Protein function is determined by protein structure which is in turn determined by the Received 25 October 2017 corresponding protein sequence. If the rules that cause a protein to adopt a particular structure are Accepted 13 April 2018 understood, it should be possible to refine or even redefine the function of a protein by working KEYWORDS backwards from the desired structure to the sequence. Automated protein design attempts to calculate Protein design; automated the effects of mutations computationally with the goal of more radical or complex transformations than protein design; ab initio are accessible by experimental techniques. design; scoring function; Areas covered: The authors give a brief overview of the recent methodological advances in computer- protein folding; aided protein design, showing how methodological choices affect final design and how automated conformational search protein design can be used to address problems considered beyond traditional protein engineering, including the creation of novel protein scaffolds for drug development. Also, the authors address specifically the future challenges in the development of automated protein design. Expert opinion: Automated protein design holds potential as a protein engineering technique, parti- cularly in cases where screening by combinatorial mutagenesis is problematic.
    [Show full text]
  • Protein Structure Analysis: Introducing Students to Rational Drug Design
    INQUIRY & Protein Structure Analysis: INVESTIGATION Introducing Students to Rational Drug Design • AGNIESZKA SZARECKA, CHRISTOPHER DOBSON ABSTRACT the steps involved in computational drug-design pipelines, a process We describe a series of engaging exercises in which students emulate the process that uses structural data for a specific protein target to rationally that researchers use to efficiently develop new pharmaceutical drugs, that of design the best effector molecule – a drug candidate. rational drug design. The activities are taken from a three- to four-hour Unlike most wet-lab experiments in molecular biology and bio- workshop regularly conducted with first-year college students and presented chemistry, these computational experiments do not require expen- here to take place over three to four class periods. Although targeted at college sive equipment or laboratory setups. The tools we describe here students, these activities may be appropriate at the high school level as well, are predominantly free online resources that are accessible via stan- particularly in an AP Biology course. The exercises introduce students to the dard Internet connection. Locally run software can also be used, topics of bioinformatics and computer modeling, in the context of rational drug design, using free online resources such as databases and computer programs. and we will recommend free and easy-to-install programs, capable Through the process of learning about computational drug design and drug of running on the majority of common platforms. The exercises optimization, students also learn content such as elements of protein structure can easily be divided between pre-lab, in-class, and homework and protein–ligand interactions.
    [Show full text]
  • Overcoming the Immunosuppressive Tumor Microenvironment in Multiple Myeloma
    cancers Review Overcoming the Immunosuppressive Tumor Microenvironment in Multiple Myeloma Fatih M. Uckun 1,2,3 1 Norris Comprehensive Cancer Center and Childrens Center for Cancer and Blood Diseases, University of Southern California Keck School of Medicine (USC KSOM), Los Angeles, CA 90027, USA; [email protected] 2 Department of Developmental Therapeutics, Immunology, and Integrative Medicine, Drug Discovery Institute, Ares Pharmaceuticals, St. Paul, MN 55110, USA 3 Reven Pharmaceuticals, Translational Oncology Program, Golden, CO 80401, USA Simple Summary: This article provides a comprehensive review of new and emerging treatment strategies against multiple myeloma that employ precision medicines and/or drugs capable of improving the ability of the immune system to prevent or slow down the progression of multiple myeloma. These rationally designed new treatment methods have the potential to change the therapeutic landscape in multiple myeloma and improve the long-term survival outcome. Abstract: SeverFigurel cellular elements of the bone marrow (BM) microenvironment in multiple myeloma (MM) patients contribute to the immune evasion, proliferation, and drug resistance of MM cells, including myeloid-derived suppressor cells (MDSCs), tumor-associated M2-like, “alter- natively activated” macrophages, CD38+ regulatory B-cells (Bregs), and regulatory T-cells (Tregs). These immunosuppressive elements in bidirectional and multi-directional crosstalk with each other inhibit both memory and cytotoxic effector T-cell populations as well as natural killer (NK) cells. Immunomodulatory imide drugs (IMiDs), protease inhibitors (PI), monoclonal antibodies (MoAb), Citation: Uckun, F.M. Overcoming the Immunosuppressive Tumor adoptive T-cell/NK cell therapy, and inhibitors of anti-apoptotic signaling pathways have emerged as Microenvironment in Multiple promising therapeutic platforms that can be employed in various combinations as part of a rationally Myeloma.
    [Show full text]
  • Drug Discovery - Yesterday and Tomorrow: the Common Approaches in Drug Design and Cancer
    Cell & Cellular Life Sciences Journal Drug Discovery - Yesterday and Tomorrow: The Common Approaches in Drug Design and Cancer 1,2 1 3 Hamad ON *, Amran SIB and Sabbah AM Mini Review 1Faculty of Bioscience & Medical Engineering, Malaysia Volume 3 Issue 1 2University of Wasit, College of Medicine, Iraq Received Date: February 27, 2018 3Forensic DNA for research and training Centre, Al Nahrain University, Iraq Published Date: April 03, 2018 *Corresponding author: Oras Naji Hamad, Faculty of Bioscience & Medical Engineering, University of Technology, Malaysia, Tel: 01121715960; E-mail: [email protected] Abstract The process of drug discovery has undergone radical changes and development over years. Traditionally, the drugs were discovered by employing chemistry and pharmacology-based cautious approach. When natural products were the most important source of drugs or drug precursors, but the conventional randomized drug research phenomenon was no longer effective at that time due to many negatives of these approaches like: high expenses of discovering new drugs, time-consuming and reduced success guarantee. Thus, with the development of the era, the concept of “Rational Drug Design” has enabled drug target identification and validation to be more specific. In addition, several novel technologies and approaches have been introducing economics, proteomics and other omics areas such as 3D QSAR, pharmacophore modeling and other, which playing a promising role in accelerating the pace of drug discovery process. Their view of the current
    [Show full text]
  • The Impact of Early ADME Profiling on Drug Discovery and Development Strategy
    ADME Profiling The impact of early ADME profiling on drug discovery and development strategy The increased costs in the discovery and development of new drugs, due in part to the high attrition rate of drug candidates in development, has led to a new strategy to introduce early, parallel evaluation of efficacy and biopharmaceutical properties of drug candidates. Investigation of terminated projects revealed that the primary cause for drug failure in the development phase was the poor pharmacokinetic and ADMET (Absorption, Distribution, Metabolism, Discretion and Toxicity) properties rather than unsatisfactory efficacy. In addition, the applications of parallel synthesis and combinatory chemistry to expedite lead finding and lead optimisation processes has shifted the chemical libraries towards poorer biopharmaceutical properties. Establishments of high throughput and fast ADMET profiling assays allow for the prioritisation of leads or drug candidates by their biopharmaceutical properties in parallel with optimisation of their efficacy at early discovery phases.This is expected to not only improve the overall quality of drug candidates and therefore the probability of their success, but also shorten the drug discovery and development process. In this article, we review the early ADME profiling approach, their timing in relation to the entire drug discovery and development process and the latest technologies of the selected assays will be reviewed. iscovery and development of a new drug is a lead finding/selection process, which in general takes By Dr Jianling Wang long, labour-demanding process. Recent a minimum of two more years. Typically, the whole and Dr Laszlo Urban Dstudies1 revealed that the average time to process is fragmented into ‘Discovery’, ‘Development’ discover, develop and approve a new drug in the and ‘Registration’ phases.
    [Show full text]
  • Setting Fair Prices for Life-Saving Drugs by Bruce A
    Virtual Mentor American Medical Association Journal of Ethics January 2007, Volume 9, Number 1: 38-43. Policy forum Setting fair prices for life-saving drugs by Bruce A. Chabner, MD, and Thomas G. Roberts Jr., MD, MSocSci Cancer drugs are big business. Worldwide sales are projected to reach $25 billion in 2006 and to increase to almost $50 billion by 2010 [1]. This represents a startling growth in a segment of the drug industry once shunned by major pharmaceutical manufacturers as too high-risk and unprofitable. While a few drug companies, notably Bristol-Myers Squibb (BMS) and Pharmatalia, made significant profits on cancer drugs between 1970 and 1990 when the first effective combination therapies came into common practice, the turning point in this industrial segment occurred in 1992 with the approval of Bristol-Myers Squibb’s paclitaxel, which became a multibillion-dollar-per-year product by 1998. To understand our current concerns with cancer drug costs and their potential effect on medical care financing and access, one needs to be familiar with the paclitaxel experience. The story of paclitaxel’s discovery and commercial development reflects both the lack of interest that industry had in cancer drugs at that time and the sudden emergence of drug cost as a social justice issue. In 1964 Monroe Wall and associates, working at the Research Triangle Institute under a National Cancer Institute (NCI) contract, isolated the active compound in paclitaxel from the bark of the common yew tree [2]. Its tortuous development, complicated by difficulties in material procurement, compound purification and formulation, delayed its entry into clinical trials until 1983, and its efficacy in treating ovarian cancer was not demonstrated until 1987 [3].
    [Show full text]
  • Incentivizing the Utilization of Pharmacogenomics in Drug Development Valerie Gutmann Koch
    Journal of Health Care Law and Policy Volume 15 | Issue 2 Article 3 Incentivizing the Utilization of Pharmacogenomics in Drug Development Valerie Gutmann Koch Follow this and additional works at: http://digitalcommons.law.umaryland.edu/jhclp Part of the Chemicals and Drugs Commons, and the Health Law Commons Recommended Citation Valerie G. Koch, Incentivizing the Utilization of Pharmacogenomics in Drug Development, 15 J. Health Care L. & Pol'y 263 (2012). Available at: http://digitalcommons.law.umaryland.edu/jhclp/vol15/iss2/3 This Article is brought to you for free and open access by DigitalCommons@UM Carey Law. It has been accepted for inclusion in Journal of Health Care Law and Policy by an authorized administrator of DigitalCommons@UM Carey Law. For more information, please contact [email protected]. INCENTIVIZING THE UTILIZATION OF PHARMACOGENOMICS IN DRUG DEVELOPMENT VALERIE GUTMANN KOCH* I. INTRODUCTION The last decades have witnessed remarkable advancements in the fields of genetics and genomics, highlighted by the successful completion of the map of the human genome in 2003.' With this achievement came scientific possibilities that, only a few decades earlier, seemed more science fiction than reality. Of these developments, pharmacogenomics is hailed by many as a panacea for problems associated with pharmaceutical drug use and development.2 The Human Genome Project (HGP) and associated research have demonstrated that all human beings share 99.9 percent of their DNA. 3 Pharmacogenomics focuses on the 0.1 percent differences between individuals and promises to allow physicians to tailor a patient's prescription according to his or her genetic profile, reducing painful and sometimes deadly side effects, ensuring appropriate dosage decisions, and targeting specific disease pathways.4 Copyright © 2012 by Valerie Gutmann Koch.
    [Show full text]