Pharmacometrics: a Multidisciplinary Field to Facilitate Critical Thinking in Drug Development and Translational Research Settings

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Pharmacometrics: A Multidisciplinary Field to Facilitate Critical Thinking in Drug Development and Translational Research Settings

Jeffrey S. Barrett, PhD, FCP, Michael J. Fossler, PharmD, PhD, FCP, K. David Cadieu, BS, and Marc R. Gastonguay, PhD

Pharmacometrics has evolved beyond quantitative analy- without such backgrounds. Given the paucity of existing sis methods used to facilitate decision making in drug training programs, available training materials, and acad- development, although the application of the discipline in emic champions, a virtual faculty and online curriculum this arena continues to represent the primary emphasis of would allow students to matriculate into one of several scientists calling themselves pharmacometricians. While programs associated with their advisor but take instruc- related fields populate and interface with pharmacomet- tion from faculty at multiple institutions, including rics, there is a natural synergy with clinical pharmacology instructors in both industrial and regulatory settings. due to common areas of research and the decision-making Flexibility in both the curriculum and the governance of expectation with respect to evolving conventional and the degree would provide the greatest hope of addressing translational research paradigms. Innovative and adapt- the short supply of trained pharmacometricians. able training programs and resources are essential in this regard as both disciplines promise to be key elements of the clinical research workplace of the future. The demand Keywords: Pharmacometrics; critical path; NIH roadmap; for scientists with pharmacometrics skills has risen sub- education; clinical pharmacology stantially. Likewise, the salary garnered by those with Journal of Clinical Pharmacology, 2008;48:632-649 these skills appears to be surpassing their counterparts © 2008 the American College of Clinical Pharmacology

he history of pharmacometrics is relatively foreshadowed the paths that the field would later Trecent, with the first citations appearing in arti- traverse covering physiologic characterization of the cles by Lee in 19711 and 1976.2 This early research guinea pig gallbladder in vitro using various probe agents such as atropine and acetylcholine1 and the quantitative characterization of neuromuscular block From the Laboratory for Applied PK/PD, Clinical Pharmacology & by tubocurarine.2 Of course, the disciplines with Therapeutics Division, The Children’s Hospital of Philadelphia, Philadelphia, which pharmacometrics can be associated, includ- Pennsylvania (Dr Barrett); the Pediatrics Department, School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (Dr Barrett); the ing basic and clinical pharmacology, biostatistics, Department of Clinical Pharmacokinetics, Modeling, and Simulation, and medicine, have much longer histories. Ette and GlaxoSmithKline, King of Prussia, Pennsylvania (Dr Fossler); KDC Group Williams3 have provided a historical context from Inc, Lawrenceville, New Jersey (Mr Cadieu); and the Metrum Institute, which the evolution of pharmacometrics can be Tariffville, Connecticut (Dr Gastonguay). Submitted for publication appreciated. More important than its history is the December 6, 2007; revised version accepted January 20, 2008. Address definition of the field itself and the rationale for why for correspondence: Dr Jeffrey S. Barrett, The University of Pennsylvania Medical School, Pediatrics Department, Abramson Research Center, Rm this discipline merits study and is likely to have 916H, 3615 Civic Center Boulevard, Philadelphia, PA 19104; e-mail: impact on medical and pharmaceutical research [email protected]. now and in the future. Several definitions for phar- DOI: 10.1177/0091270008315318 macometrics have been proposed. Early definitions

632 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS tended to focus on population-based methodologies, specifically population pharmacokinetics (pop-PK), Health Economics incorporating assessment of uncertainty as a unify- Regulatory ing topic. More recently, pharmacometrics has been Clinical Science described as the science of developing and applying Pharmacology mathematical and statistical models to characterize, Computer understand, and predict a drug’s PK, pharmacody- Science Statistics namic (PD), and biomarker-outcome behavior.3 This, Medicine too, is likely limiting given the scope of the disci- Pharmacology pline’s recent applications. A still broader definition Ethics Computational will be proposed in this treatise. Methods The salient point of the discussion on pharmacometrics is the explicit recognition of this field as a Engineering bridging discipline that facilitates translation of com- Pharmaceutics plex biologic processes and communicates them in a Marketing quantitative manner. Figure 1 illustrates the relationship between pharmacometrics and related disciplines (inner circle) as well as other fields (outside Figure 1. Multidisciplinary influence on the field of the circle) that may often interface with those pharmacometrics. engaged in pharmacometrics research, particularly within the confines of a drug development setting. very much in keeping with the intention of the While some of these external disciplines will never National Institutes of Health (NIH) Roadmap,5 which come into play for many pharmacometricians, exam- seeks to address the need to advance the under- ples of pharmacometric interface with each of these standing of the complexity of biological systems: disciplines can be shown and are easy to appreciate “Future progress in medicine will require a quanti- given the public perception of postmarket surveillance, tative understanding of the many interconnected the cost of drugs in general, and late-recognized tox- networks of molecules that comprise our cells and icity associated with marketed drugs that sometimes tissues, their interactions, and their regulation. We results in their removal from the market. As with need to more precisely know the combination of many relatively new fields, there is a temptation to molecular events that lead to disease if we hope to nest them as subspecialties within a broader defini- truly revolutionize medicine.” tion of the more established disciplines. This indeed Likewise, the discipline was specifically cited by may be a reasonable strategy to both nurture and the US Food and Drug Administration (FDA), along mentor those engaged in the research and fund or with advances in clinical pharmacology, as essential otherwise financially support the actual research. If elements for innovative drug development in its pharmacometrics research is to warrant sustained Critical Path Initiative.6 interest from scientists investing in these skills and We provide herein a critique of the pharmacomet- the institutions seeking to benefit from the actual rics discipline, including its scope, the interplay of research, it must be viewed as a complete discipline related disciplines, diversity of the career paths and not a subfield of clinical pharmacology. More defined by pharmacometrics expertise, and avail- importantly, the rapidly expanding complexity of the able training courses, programs, and materials. We underlying science mandates practitioners to focus also explore hiring data collected during the past 10 on this as a unique field in order to maintain compe- years and examine the financial benefit of pharma- tency for this bridging discipline. cometrics skills via comparisons within and across While the demand for pharmacometrics scientists various “homes” for pharmacometricians. Finally, is currently high among industrial and regulatory we propose a curriculum that accommodates the communities, there is also a growing appreciation diversity of skill sets necessary to graduate scientists for pharmacometrics skills as part of academic med- with formal pharmacometrics training. ical and translational research environments.4 Bridging disciplines as a means to tie concepts and DISCIPLINE DEFINED research aims together are commonly identified as necessary to avoid gaps in grant submissions reliant Pharmacometrics can be defined as that branch of on quantitative assessment and forecasting. This is science concerned with mathematical models of

FORUM 633 BARRETT ET AL biology, pharmacology, disease, and physiology used simulations to probe the design parameter space is to describe and quantify interactions between xeno- likewise inherently Bayesian. biotics and patients, including beneficial effects and Perhaps the easiest way to define the discipline is side effects resultant from such interfaces. This def- through examples. One of the most visible applica- inition more broadly frames the scope of the disci- tions of pharmacometrics is the integration of popu- pline than earlier versions and at the same time lation-based pharmacokinetics/pharmacodynamics illustrates the obvious connection with other disci- (PK/PD) models with a clinical trial simulation plines. As previously discussed, pharmacometrics is model from which trial design and execution can be indeed a bridging discipline. The nature of the explored relative to performance and outcomes. This bridges built is somewhat dependent on the setting. approach has the added benefit of exploring doses, Drug developers are naturally aligned with this con- regimens, and compliance patterns outside of histor- cept because of the similarity with the phases of ical patient experience as well as clinical assump- drug development and the milestones and decision tions regarding the exposure-response-efficacy criteria that must be met for drug candidates to relationship. Excellent published examples exist for progress into later development phases. The acade- capecitabine (5′-DFUR specifically),7,8 docetaxel,9,10 mic clinical researcher is likewise often confronted and raloxifine,11-13 with many more conducted but as with the need to use data from various sources yet unpublished. Another area of great impact is the (experimental biology, preclinical models of disease) use of modeling and simulation to facilitate drug can- in order to evolve translational clinical studies in a didate selection. Pharmacometrics in this regard has therapeutic area. The regulatory pharmacometrician been applied both preclinically using in silico14 is also faced with bringing together data from vari- approaches and in animals15 and clinically in ous sources (preclinical and clinical data, literature patients.16-18 Through the process of evaluating and data, other regulatory submissions of similar thera- comparing drug candidate characteristics, valuable pies) in order to help inform regulatory decisions. information regarding an agent’s therapeutic window On a fundamental level, however, we are really only can be identified as well as the probability that such referring to the sequence and nature of scientific information can be generalized across class or across inquiry and the process by which interrelated and agents with similar homology. One of the most excit- sequential experiments are designed, planned, and ing areas of applied pharmacometrics research is in executed. Whether in industry, academia, or regula- the area of disease progression; disease progression tory, pharmacometrics scientists are at the center of models for HIV,19 osteoporosis,20 multiple sclerosis,21 the translational medicine paradigm. and rheumatoid arthritis22-24 offer great potential to While the discipline is not necessarily aligned provide new targeted therapies. with specific methodologies or techniques, pharmacometrics is clearly associated with the construction PREQUISITES AND ESSENTIAL SKILL SETS of models. The taxonomy of models is rich, of course, but the translational nature of much of the Pharmacometrics is generally perceived as a disci- underlying data and research objectives is, at least pline requiring graduate education. Hence, potential conceptually, Bayesian. An important truism is that students matriculate from various feeder disci- the design of any experiment is conditioned upon plines. To date, pharmacy remains the primary the results and understanding of previous experi- source of pharmacometricians. This, in part, is due ments. The process is inherently Bayesian. While to the affiliations of many of the pioneers of this the process may be Bayesian, the application of field but is also related to the origin of related fields Bayesian principals in drug development or in basic of study from which pharmacometrics has evolved and clinical research has not been the approach (PK, PD, population PK/PD, etc). While some may most commonly taken. In many cases the sequence contend that these are subspecialties of clinical of experiments has been governed by a more conser- pharmacology, the majority of actual training in vative approach often reliant upon empirical criterion these areas has largely come from pharmacy curric- and experimental milestones defined by marketing ulae. Other feeder disciplines include pharmacol- requirements and not prior information. While the ogy, statistics, engineering, and medicine. It is also pharmacometrics discipline is not exclusively mar- evident that many have come into this field after ried to Bayesian approaches, the concept of model already completing advanced degrees in one or more construction and refinement and subsequent use of disciplines. This, too, highlights the difficulty in

634 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS constructing a core curriculum for a pharmacomet- directly out of school to pharmaceutical research is rics degree, as the application of the approaches and unlikely. Hence, most engineers in the field have techniques central to the discipline implies greater arrived in pharmacometrics by serendipity. Because than cursory appreciation of biological systems and of the need for statisticians in biomedical research, disease etiology. This would be a difficult feat to they are more likely to come into contact with phar- accomplish in the typical 4-year undergraduate macometrics scientists, which may explain the large program. Table 1 provides a SWOT (Strengths, number of statisticians in the field as compared with Weaknesses, Opportunities, and Threats) analysis of engineers. the various feeder disciplines. While the comparison highlights the diversity of the likely incoming CAREER OPPORTUNITIES student pool, it also represents the breadth of the subject matter, which defines the pharmacometrics Opportunities for scientists with modeling expertise discipline. have increased over time, and there is evidence that As stated above, pharmacy has been the primary those with these skills actually garner higher discipline that supplies candidates for pharmaco- salaries. Over time, job descriptions have begun to metrics training. The typical pharmacy curriculum identify very specific skills now aligned with what is rich and diverse, integrating physiology, pharma- we associate as pharmacometrics expertise. We have cology, and therapeutics along with basic sciences examined the hiring practices of pharmaceutical (chemistry, biology, math) and more practical phar- industry departments that would hire individuals macy courses (PK, drug delivery, etc). Hence, it with such training (principally, clinical pharmacol- requires the least additional preparation with ogy and clinical PK groups) during the past 10 years. respect to obtaining an appreciation for the pharma- In total, 62 hires from 1997 through October 2007 cometrics discipline and the vision of its applica- were evaluated and categorized according to hire tion. The missing didactic components would be date, department making the hire, degrees of the decidedly computational and methodology based. candidate, region of hire (West Coast, East Coast, Medicine is also a discipline that seems to be a rea- Midwest, Europe, and other), years of experience, sonable fit as background to the advanced study in and starting salary (US dollars, unadjusted for infla- pharmacometrics. Like pharmacy, students from tion). Data were obtained from a single recruiting medical backgrounds would need additional train- firm (The KDC Group) with expertise in the place- ing in numerical methods. ment of these positions. In addition, the applicants The discipline of pharmacology provides a strong were categorized as belonging to one of the follow- foundation in life sciences applied to the study of ing classes: PK, PK with modeling and simulation xenobiotics, although the application to clinical set- expertise (PK-MS) background, clinical pharmacol- tings is not always a focus of contemporary molecu- ogy (CP), clinical pharmacology with modeling and lar pharmacology. The mechanistic basis for drug simulation expertise (CP-MS), and pharmacometrics actions is a potentially attractive background for (PM). The assignment of pharmacometrics as a cate- understanding disease processes and systems gory was based on the hiring manager specifically biology in general. As with pharmacy and medicine, defining the position as pharmacometrician, while courses in computational and methodologic tech- the other categories were assigned based on the can- niques are generally lacking in the graduate pharma- didate’s abilities and skills. Our contention is that cology curriculum. A disturbing trend is that salaries have increased faster than the rate of infla- approximately 40% of the PhD pharmacology tion and are somewhat responsive to industry trends programs in the United States require no formal and milestones in quantitative analysis and on the coursework in PK.25 assessment of regulatory authorities (NIH, FDA, etc). Engineering and statistics produce individuals For example, creation of the pharmacometrics group with strong, analytic problem-solving skills. A key within the FDA, subsequent FDA guidances refer- competency that engineers often possess is the abil- ring to pharmacometric techniques, and the creation ity to conceptualize physical systems and describe and expansion of contract research organizations them quantitatively either through experimentation (CRO) to provide pharmacometric services are all or design and modeling. Unfortunately, courses in contributing factors to the increase in salaries the life sciences are not prerequisites for any of the beyond the rate of inflation. major engineering disciplines, nor are they required Of the 62 hires analyzed, 51 were PhDs, 5 were for a statistics degree. Exposure of the typical engineer PharmD/PhDs, 2 were PharmDs, 1 had an MS, and 3

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Table I Strengths, Weaknesses, Opportunities, Threats (SWOT) Analysis of Feeder Disciplines as Backgrounds for Incoming Students to Pharmacometrics

Strengths Weaknesses Opportunities Threats

Pharmacy Foundation in math, Little Math electives easily Competition for chemistry, physics, experimentation accommodated as students by biology No programming necessary high-paying Principles of drug action, Only basic Statistics, study pharmacy jobs pharmacology, and statistics design, Often sparse funding biochemistry understanding programming, and opportunities Anatomy and physiology simulation courses Applied PK and PK/PD, would fit well and therapeutics into existing Appreciation for drug curriculum delivery and input in general Pharmacology Foundation in math, Little or no Math electives easily Focus on molecular chemistry, physics, problem-solving accommodated as and cellular systems biology No programming necessary already perceived Pharmacology related to Basic statistics Statistics, study to dilute field various drug targets only design, from whole organ (organ systems/ Little or no PK programming, and systems—may make receptors/enzymes) and PK/PD simulation courses transition to Anatomy, physiology, would fit well pharmacometrics human pharmacology into existing too far away curriculum Medicine Principles of drug action, Little Math electives easily Competition for pharmacology, and experimentation accommodated as students by biochemistry No programming necessary high-paying clinical Anatomy and physiology Little or no Statistics, study specialty jobs Therapeutics problem-solving design, High debt load often Many programs programming, and forces graduates have no simulation courses into high-paying pharmacology would fit well clinical specialties into existing Funding opportunities curriculum Engineering Foundation in math, Little or no life Life sciences track Trainee interest in chemistry, physics sciences necessary the field different Chemical kinetics; No biochemistry (prerequisites for from engineering reaction mechanisms No obvious some engineering Competition for (ChemEng only) application to disciplines would trainees Applied higher order math; living systems be substantial) problem-solving to in general Additional pharmacy model physical systems Modeling focused electives may be Experimental design and on deterministic helpful statistics solutions; Programming little emphasis on uncertainty Statistics Foundation courses in math Little or no life Life sciences track Competition for Applied higher-order math sciences necessary; may be trainees and problem-solving No biochemistry difficult to fit into Experimental design and No obvious existing program statistics application to Additional pharmacy Programming living systems electives may in general be helpful

PK, pharmacokinetics; PD, pharmacodynamics; ChemEng, chemical engineering.

636 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS

3 Number

0 3 1997 1999 2001 200 2005 2007 Figure 3. Relationship between date of hire, years of experience Year and starting salary for clinical pharmacology and clinical phar-

PK (Pharmacokinetics) macokinetics candidates placed between 1997 and 2007. Salary PK-MS (Pharmacokinetics with modeling and simulation skills) data provided by the KDC Group. CP (Clinical Pharmacology) CP-MS (Clinical Pharmacology with modeling and simulation skills) PM (Pharmacometrics) and hire date. Not surprisingly, there is a clear trend Figure 2. Summary of hiring trends for clinical pharmacology between years of experience and starting salary early and clinical pharmacokinetics candidates placed between 1997 in this sampled population. This relationship is not and 2007. Salary data provided by the KDC Group. as well defined in later years, consistent with the onset of PM hires. This would seem to be supported were MDs. Years of experience ranged from 0 to in Figure 4A which shows the salary versus years of more than 20 with a mean (SD) of 6.5 (5.5) years. experience correlation for each of the subclasses. Most of the hires were placed in the East Coast of the Both the PK and PK-MS groups show the expected United States (n = 40; 64.5%) with the remainder correlation, but the trend for PMs is less steep, sug- spread across the West Coast (7), Midwest (4) and gesting that years of experience is a less significant Europe (9); 2 hires were outside these primary factor on predicting starting salary. regions. Figure 2 shows the hiring rates for each of There are several interpretations possible from the categories listed over time (1997-2007). While these observations. It could well be that experience the placement of general PK skills seems steady in is less important than demonstrated competence in this limited dataset, the demand for pharmacomet- this area. It could also be that these positions reflect rics positions can be seen to emerge by 2000 and has a team-driven alignment in more of a matrix organi- quickly increased during the past 7 years. This zation as opposed to a hierarchical role. It would demand would appear to be even greater if one pools certainly seem that all applied sciences are becom- the other categories (PK-MS and CP-MS) in which ing more matrix-oriented, and it is certainly a factor candidates were hired with modeling and simula- in the various training grants that seek to educate the tion skills although the position was not formally “workforce of the future.” The trend likely also defined for a “pharmacometrician.” reflects the short supply and the need for potential The examination of salary impact is more com- employers to pay more for less experienced candi- plex as years of experience, geographical considera- dates. Figure 4B shows the salary versus hire dates tions, degree (MD vs PhD and PharmD), and hiring for the PK, PK-MS, and PM subgroups only (CP and department are all perceived to be factors in the CP-MS having too little data to include on such determination of starting salary. Starting salaries dur- timelines). Pharmacometric hires do not appear ing this 10-year period ranged from $60K to $230K until 2000; in all but 1 year, the average salary for US dollars with a grand mean of $119,400. The data PMs exceeds that of PK-only scientists. While PM are too sparse for a rigorous examination of these scientists had an average of 2 more years of experi- factors, of course, but some interesting relationships ence, the obvious confounding is not expected to can be visualized. Figure 3 shows a 3-dimensional bias this interpretation. Future tracking of this trend histogram of starting salary against years of experience will assess the validity of this observation.

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results of the full survey are contained in the appen- A dix and available on the Web as well (http://www PMetrics .med.upenn.edu/kmas/). 200000 In any event, these results, along with the pleas 100000 from industrial26-29 and regulatory30,31 stakeholders, support the belief that pharmacometrics training PK PK with M&S 200000 and skills are still in high demand. While these 2 communities (regulatory and industrial) can be 100000

Salary (USD) identified as long-standing consumers of pharmaco-

Clin Pharm Clin Pharm with M&S metricians, it also is becoming evident that this dis- 200000 cipline may benefit academic research as well. The recent emphasis on translational research and the 100000 specific willingness of funding agencies to support such efforts has allowed academics to create 0 10 20 Experience (year) research teams more poised to deliver bedside-to- bench strategies and outcomes. Likewise, the NIH 5 B Roadmap initiative and the Clinical and 200000 Translational Science Awards (CTSA) program32,33 create infrastructure opportunities for academic 175000 medical research communities to both grow phar-

150000 macometrics as a bridging discipline and promote novel research reliant upon innovative pharmaco- 4,34 125000 metrics approaches. This may well provide the chance to construct the ultimate academic home for Salary (USD) Salary 100000 a pharmacometrics degree program (discussed later).

75000 CURRENT TRAINING

50000 AND EDUCATIONAL RESOURCES 1996 1998 2000 2002 2004 2006 2008 Hire Date At the moment there are relatively few options with PK PK with M&S PMetrics respect to formal didactic training specifically in pharmacometrics. Several universities, pharmaceutical industry research groups, and even the FDA offer Figure 4. Salary versus years of experience (A) and hire date (B) training fellowship programs, but these are not for clinical pharmacology and clinical pharmacokinetics candidates placed between 1997 and 2007 examined by subgroup degree-granting nor do they follow any established class. PMetrics, pharmacometrics; PK, pharmacokinetics; M&S, curriculum. The State University of New York (SUNY modeling and simulation skills; Clin Pharm, clinical pharmacol- Buffalo) launched the first MS degree program in phar- ogy. Salary data provided by the KDC Group. macometrics in 2001. This represents a milestone for the discipline, and it is hoped that other institutions follow suit. Courses in pharmacometrics and related It is clear that the demand is still great for scien- subjects are offered at the universities of Minnesota, tists with pharmacometrics skills. Recently, we sur- Auckland (New Zealand), Uppsala (Sweden), veyed the members of the NMUSERS listserv Tennessee, and the China Pharmaceutical University (NONMEM users database) with one question (Nanjing), but these are mostly electives offered as specifically addressing hiring expectations of the part of other programs. A pharmacometrics track is upcoming year. Of those surveyed, 14.2% (n = 29) offered as part of the experimental medicine program stated that their company was likely to hire more at the University of Minnesota. The University of than 2 PMs, and 25.5% (n = 52) stated that their Pennsylvania will offer a similar track as part of its company would hire 1 to 2 candidates next year. translational medicine program within the School of Many (43.1%; n = 88) answered that there would be Medicine. Table 2 describes the extent of the university- positions available in the future but not presently; based training available worldwide along with the only 17.2% (n = 35) answered that their company faculty participating in this effort. While we have was not likely to hire additional personnel. The attempted to be inclusive, we recognize that this is not

638 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS

Table II Academic Sites and Universities Offering Curriculum in or Related to Pharmacometrics

University/Training Center Program Offerings and Faculty

Uppsala University (Sweden) Mats Karlsson, Niclas Jonsson, Anders Grahnen (http://www.farmbio.uu.se/upload/avd5/Pharmacometrics/) Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy, Pharmacometrics Research Group University of New York at Buffalo Bill Jusko, Don Mager, Joe Balthasar, Alan Forrest (http://pharmacy.buffalo.edu/admissions_psci_grad_ MS in Pharmacometrics since 2001, Department pharmacometrics.shtml) of Pharmaceutical Sciences University of Minnesota Dick Brundage (http://www.pharmacy.umn.edu/ecptrack/home.html) Graduate program track in experimental and clinical pharmacology Anhui Center for Drug Clinical Evaluation, Wannan Rui-yuan Sun Medical College (China) Courses in pharmacometrics offered since 1982 Auckland University (New Zealand) Nick Holford (http://www.fmhs.auckland.ac.nz/faculty/postgrad/ Pharmacometrics courses offered through the courses/course_all.aspx?subject=MEDSCI) Medical and Health Sciences Department University of Otago (New Zealand) Stephen Dufful (http://pharmacy.otago.ac.nz/pages/research.html) Workshops and tutorials in basic statistics, (http://www.paganz.org/default.asp?id=42&keuze=meeting) calculus, nonlinear regression and NLMEM, Bayesian analysis, MCMC, design of experiments, pop-PK, pop-PK/PD and PK/PD University of Washington Paolo Vicini (http://depts.washington.edu/rfpk/training/workshops.html) Workshops on Nonlinear Regression to Mixed Effects Models University of Lyon (France) Pascal Girard Faculté de Médecine, Université Claude Bernard Albany College of Pharmacy George Drusano (http://www.acp.edu/academics_pri.html) Hands-on access to the full spectrum of drug (http://www.ordwayresearch.org/profile_drusano.html) development University of Tennessee Bernd Meibohm (http://pharmacy.utmem.edu/pharmacy/pharmsci/ College of Pharmacy, Pharmaceutics Department pharmsci.html) courses University of Pennsylvania Jeff Barrett (http://www.med.upenn.edu/kmas/) Postdoctoral mentorship in pharmacometrics University of Pennsylvania will provide graduate program in Pharmacometrics in fall 2008 INSERM (France) France Mentre INSERM U738, Department of Epidemiology and Biostatistics, Bichat University Hospital, Paris University of Pittsburgh Robert Bies (http://www.pharmacy.pitt.edu/directory/dir_grad.lasso?Last=BiesR) Graduate student mentorship in pharmacometrics University Paris-Sud (France) Marc Lavielle Laboratory of the University Paris-Sud (Orsay) University of California at San Francisco Howard Lee, Nancy Sambol, Davide Verotta, (http://cdds.ucsf.edu/cdds_ps/) Carl Peck (http://cdds.ucsf.edu/programs/courses.php) Training and education of translational and clinical investigators in PK, PD, and pharmacometrics University of Queensland School of Pharmacy (Australia) Bruce Green, Carl Kirkpatrick PhD and postdoctoral training in pharmacometrics University of Southern California, Department of David D’Argenio Bioengineering PhD and postdoctoral training University of Gothenburg, Department of Johan Gabrielsson and Gunnar Tobin Pharmacology at the Sahlgrenska Academy (Sweden) Master’s program in PKPD (quantitative (http://www.pharmguse.net/advanced/advanced-courses.html) pharmacology) Martin-Luther-Universitaet-Halle-Wittenberg, Charlotte Kloft and Wilhelm Huisinga the Freie Universitaet Berlin (Germany) PhD fellowships in pharmacometrics and (http://www.pharmacometrics.de) computational disease modeling

MS, master’s of science; NLMEM, nonlinear mixed-effect modeling; MCMC, Markov Chain Monte Carlo; pop, population; PK, pharmacokinetics; PD, pharmacodynamics.

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Table III Some Centers Providing Training Courses

LAPK Roger Jelliffe, Alan Schumitsky (http://www.lapk.org/#education) Workshops, short courses, technical reports, symposia, fellowships, and scientist-in-residence programs Metrum Institute Marc Gastonguay, Bill Gillespie, et al (http://www.metruminstitute.org/training/training.html) Pop-PK/PD, NLMEM, Bayesian Methods, R, software qualification Pharsight Corporation Dan Weiner, Kevin Dykstra, Rene Bruno, et al (http://www.pharsight.com/training/training_upcoming.php) PK/PD modeling, mixed-effect (pop-PK) modeling, trial simulation, software Fisher/Shafer NONMEM Workshop Dennis Fisher, Steve Shafer, Pamela Flood (http://www.nonmemcourse.com/) Introduction to R and NONMEM workshops EMF Consulting Joachim Grevel, Elaine Fuseau (http://www.emf-consulting.com/) NONMEM training course Exprimo Janet Wade (http://www.exprimo.com/pastcourses.asp) Population analysis using NONMEM Globomax/ICON Tom Ludden, Bill Bachman (http://www.globomax.net/products/workshops.cfm) NONMEM and IVIVC http://www.icondevsolutions.com/workshops.htm Cognigen Ted Grasela, Jill Fiedler-Kelly, et al (http://www.cognigencorp.com/cognigen.our-services.html) Instructor-led and Web-based training services

LAPK, Laboratory for Applied Pharmacokinetics; PK/PD, pharmacokinetics/pharmacodynamics; NLMEM, nonlinear mixed-effect modeling; pop, population; IVIVC, in vitro-in vivo correlation. always possible given the dynamic nature of univer- Bonate and Pharmacometrics: The Science of Quanti- sity course offerings. We have tried to identify tative Pharmacology,3 a collection of articles on phar- programs in which a commitment to pharmacometric macometrics edited by Ene Ette and Paul Williams, training can be established, as opposed to an appreci- have provided the first books targeted to the pharma- ation for pharmacometrics topics (eg, population PK). cometrics community. Many excellent books on PK, In the absence of established training programs PK/PD, CP, and other foundation disciplines exist; with didactic curriculum, many potential students these serve as prerequisite reading for those studying and trainees attend focused workshops on various pharmacometrics. Additional teaching-oriented texts pharmacometrics-related topics. Often these topics are still needed however, particularly those that pro- are application-based with some, but often limited, vide a more structured presentation of core concepts introductory material on the approach or methodol- in a common voice. Table 4 lists some of the avail- ogy. In addition, these workshops have implicit pre- able online resources for those interested in phar- requisite knowledge assumed for the student to macometrics. Given the growth of the discipline, the benefit from the training. Table 3 provides a listing availability of online content is likely to expand. of some of the prominent workshops and training Hopefully, this will include online training and courses offered by universities, academic/nonprofit courses as well. CROs, and for-profit corporations. Of course this list is not all inclusive, but it does highlight the nature PROPOSAL FOR TRAINING of the workshops offered as well as the instructors that provide such training. Recalling a conversation with the late Dr. John Another aspect of training is the availability of Wagner, he stated, “The only way to learn pharma- training materials and resources. These would include cokinetics is to do pharmacokinetics” (oral commu- textbooks, white papers, journal articles, and com- nication, June 1987). This is true for many technical puter-based training materials (Web-based tutorials and applied disciplines and is certainly true for and video-based lectures, workshops, and courses). pharmacometrics. Nonetheless, it is helpful to learn In this area as well, the materials are woefully inad- from someone and have materials from which knowl- equate, although recent additions have been extremely edge can be gained. While many wonderful exam- valuable. Specifically, texts on Pharmacokinetic- ples of pharmacometrics applications exist, most Pharmacodynamic Modeling and Simulation35 by Pete of these have been embedded within the internal

640 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS

Table IV Web Sites Containing Information on Pharmacometrics

Site (URL) Content

CDDS General information (http://gumc.georgetown.edu/departments/ clinicalpharmacology/ClinicalPharmacology TrainingProgram/trainingprogram.html) ACCP Web aid for pharmacometrics training; terminology (http://accp1.org/pharmacometrics/index.html) defined; some basic examples provided University of Auckland General background and links to useful resources on the (http://www.health.auckland.ac.nz/pharmacology/staff/ Internet for learning more about pharmacometrics nholford/pkpd/pkpd.htm) NONMEM UsersNet Archive Discussions/queries posted to the NONMEM Users (http://www.cognigencorp.com/nonmem/nm/) Network; organized into threads, identified by a subject line and sorted from most recent posting to most ancient PAGE Many links to services, related sites, research initiatives (http://www.page-meeting.org/default.asp) PK/PD Bookmarks PK/PD groups, Web sites, courses, articles, book (http://pkpd.wordpress.com/feed/) chapters, tutorials, training, workshops, software, people, related journals, books

CDDS, Center for Drug Development Science; ACCP, American College of Clinical Pharmacology; PAGE, Population Approach Group in Europe; PK/PD, pharmacokinetics/pharmacodynamics.

Table V Core Functions of Pharmacometricians in Various Settings

Setting Core Functions Impact/Deliverables Collaborations

Regulatory Facilitate regulatory review Improved interaction with Pharmaceutical sponsors of sponsor applications medical reviewers Medical and statistical Verify label claims and sponsors reviewers Evaluate dose recommendations Dose recommendation Academic thought leaders Evaluate safety/efficacy claims Study designs Academia Support/consult industry New biomarkers/endpoints Pharmacometrics scientists applications Disease process/progression across institutions Translational research New tools Grant team members Methodology/IT More trained Statisticians, progranmmers Developmental population PK/PD pharmacometricians Neonatologists, Teaching new students pharmacologists Industry PK modeling Candidate selection Project team members Concentration-effect relationship Dose selection FDA/global regulatory (PK/PD modeling) Defined therapeutic window authorities CTS for optimal trial design Identification of “at risk” CROs Simulation studies to subpopulations requiring Academic thought leaders evaluate/extrapolate drug dose modifications Senior management/decision performance for various scenarios Improved studies (may makers Candidate selection obviate need for study)

IT, information technology; PK/PD, pharmacokinetics/pharmacodynamics; CTS, clinical trial simulation; FDA, Food and Drug Administration; CRO, contract research organization. decision making of drug makers or regulators with be published highlighting the value of the pharma- the details of the science masked as intellectual cometrics application in industrial and regulatory property or due to the proprietary nature of the sub- decision making, these are highly summarized. They mission process. While case studies have begun to do, however, serve as evidence of the application

FORUM 641 BARRETT ET AL

Human Stat Core Electives Pharmacology Core • PK/Biopharmaceutics • Regression Analysis • DMPK & Drug Transport • PD/Pharmacology • ANOVA • Drug Development • Disease Therapeutics • Experimental Design • Regulatory Science • Quantitative Bio analysis • Clinical Trial Design • Decision Analysis • Monte Carlo Methods • Special Programming Topics (R, SAS, SPLUS, NONMEM, PERL, Pharmacometrics Programming Core nonparametric algorithms, etc) Core

• Pop-PK • Computational Methods/Application • Clinical Trial Simulation • Intro to Statistical Programming • Bayesian Methods & Approaches in Medicine

Figure 5. Curriculum proposal for advanced degrees in pharmacometrics. PK, pharmacokinetics; PD, pharmacodynamics; ANOVA, analysis of variance; DMPK, drug metabolism and pharmacokinetics; Pop-PK, population pharmacokinetics. and the demand for the skill. Holford and Karlsson36 While a master’s program would be the initial have recently proposed a basic pharmacometrics focus in order to demonstrate the requisite data on curriculum recognizing the emphasis of the discipline demand for the program, student and faculty feed- on quantitative pharmacologic principles. Their pro- back, and outcomes from graduates, a PhD program posal also acknowledges clinical trial simulation would be the ultimate goal. Of course, there would be and disease progression modeling as key techniques training consistent with the current T32 and K to be mastered by their students. Their proposal falls (instructional training for pre- and postdoctoral and somewhat short as a model curriculum for a graduate- career development support grants, respectively) level degree in pharmacometrics and does not address mechanisms for academic physician tracks the diversity of students coming into this area. (http://www.niaid.nih.gov/ncn/training/advice/inde Given the multidisciplinary influences on this x.htm) consistent with the CTSA mission. Certificate field, it is difficult to develop one curriculum for training is also possible for those with terminal such a diverse collection of feeder disciplines. We degrees in medicine, pharmacy, or a related scientific envision several curriculum “cores” from which discipline, who do not desire or need the in-depth electives would be drawn, with the primary phar- training outlined in Figure 5. Lertora and Atkinson37 macometrics core containing mandatory courses. have discussed the benefit of hands-on research train- The cores themselves would fall into 4 categories: ing coupled with didactic courses as part of CP edu- clinical pharmacology, statistics, pharmacometrics, cation and training at NIH. They identify 5 modules and computational/programming (Figure 5). The key (PK, drug metabolism transport, assessment of drug to the program would be flexibility, with students effects, optimization and evaluation of patient ther- from different backgrounds taking courses that apy, and drug discovery and development) from their address areas which were not emphasized in their Clinical Pharmacology Research Associate Training previous training. For example, students coming (ClinPRAT) program used to accommodate a growing, into the pharmacometrics program from a statistics broader audience than the program originally background would take courses emphasizing phar- intended. An extremely valuable part of this program macology and therapeutics, as their exposure to these is the extramural participation from academic, pri- disciplines in a traditional statistics setting would vate, and governmental institutions. Eighteen remote likely be minimal. sites were listed as having participated in telecasts for

642 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS the “Principles of Clinical Pharmacology” course hardware and other proprietary software, as well as offered in 2006-2007. Hence, the value in educating system administration costs, still remain. These, too, and training extramural researchers as an extension of could be shared if the pharmacometrics community the NIH roadmap and CTSA program is being demon- could pool resources and if industry would assist in strated by the NIH itself. Future CP training programs the funding for initial capital expenses as well as offered by the NIH are likely to advocate a combined maintenance and administration costs. With current training curriculum that would incorporate CP and Web-enabled technologies, it is feasible that a high- enhance translational research in pharmacology and performance grid computing/data center could be therapeutics. It would likewise seem logical that a assembled with necessary software and administered strategy for pharmacometrics training not only follow by a core group, with access made available to phar- such approaches but develop partnerships with CP macometric training programs. Such an environment and translational medicine research faculty to extend would support complex modeling and simulation the training in areas of overlap. applications that are not currently feasible on most In general, universities have been slow to embrace academic computing resources (eg, stand-alone per- this discipline, as evidenced by the relative paucity sonal computers) and would facilitate the develop- of formal degree-granting programs listed in Table 2. ment of online training modules,39,40 providing an There are perhaps many reasons for this, but the pri- easier mechanism to share model solutions and work mary one is the perception that pharmacometrics is on coding problems in a more dynamic manner. In an applied science and therefore not fundable by NIH all likelihood such an environment would also pro- or other granting agencies. Funding concerns affect mote the continued development of algorithms and many of the core disciplines as well. The pharmacol- methodology-based research given the mobilization ogy community seems to have retooled many of the community to a shared computing platform at programs believing that in vitro models and cell least for training and education. biology have become the driving force for funding research, training scientists, and for drug discovery THE FUTURE OF THE DISCIPLINE and development.38 There is also intense competition for pharmacometrics-trained scientists, and the phar- There are no excesses of engineers, clinical pharma- maceutical industry seems to be winning the battle cists, statisticians, and physicians to provide incen- for these individuals, with relatively few of them tives for those in these disciplines to automatically going into academia. Given these realities, there is pursue further training. Likewise, the path to phar- certainly a strong rationale for a “virtual” adjunct fac- macometrics, or CP for that matter, will continue to ulty comprised of scientists in academic, industrial, be the road less traveled. In the case of pharmaco- and regulatory settings who will take an active role in metrics, a few signposts and a plowed pathway the training and development of future pharmacome- would help, as the manner in which scientists cur- tricians. In addition to leveraging this group of indi- rently arrive at this destination is still circuitous and viduals, the other benefits of a virtual faculty include unmarked for many. To this end, those currently a more diverse perspective on the discipline, with a invested in the field need to provide guidance with broad array of skills and interests and perhaps a respect to training the next generation of pharmaco- greater emphasis on real-world problems and actual metricians and contribute to the materials from drug development challenges. which these individuals will be trained. Finally, a curriculum in pharmacometrics must In the absence of adequate training programs, some certainly rely on significant computational resources, companies have invested in internal postdoctoral train- and the institutions supporting the discipline must ing efforts, most notably Pfizer and GlaxoSmithKline continually invest in high-end platforms/hardware (GSK). These would appear to be successful from the and software, including licenses for some of the key company’s perspective as the majority of these algorithms (eg, NONMEM, TS2, FORTRAN, trainees have indeed become employed by the host Mathematica, Matlab, SAS, R, SPLUS, nonparametric- company. These, of course, have capacity limita- based algorithms, etc). The current availability of robust tions and also do not serve the external community, and widely used open-source tools, such as statistical/ but they do reflect the appreciation for the discipline modeling/simulation software (eg, R, OpenBUGS, and the short supply of trained candidates. More Octave), operating systems (eg, Linux, BSD), compilers importantly for the company, they deliver hands-on, (GNU), and distributed computing tools (eg, Sun mentored training in the skill set they need and GridEngine, OpenMosix) does make high-performance provide an immediate avenue for career develop- computing more accessible than in the past, but ment for the scientists trained in this manner. While

FORUM 643 BARRETT ET AL recognizing the financial pressure that the pharma- complementary organizational structures, comput- ceutical industry finds itself under, we feel it is in ing infrastructure, and support investment and the best interest of the industry as a whole to expand processes that promote critical thinking without the funding of pharmacometrics programs, both pre- operational overhead (study conduct, reporting, data and postdoctoral. Providing incentives for their management, etc). The demand for these skills is experienced scientists to participate in these train- likely to improve the current disparity among the ing programs (or at least no disincentives) would various research and development environments also be a worthwhile investment. and the CRO industry as well. Given the global reg- A bigger challenge will be to convince universities ulatory environment investments in pharmacomet- to develop graduate-level pharmacometrics programs. rics,43,44 it is only natural that pharmacometrics-naïve Although the need is clearly demonstrable, schools companies develop or acquire complementary skills may be reluctant to invest the time and money that if only to maintain a dialogue with regulators. will be required to hire experts in the field as faculty Academic researchers have a less certain career (who are already scarce) and support them until path in pharmacometrics. There are certainly numer- external funding can be established. Again, it is our ous opportunities for the discipline in translational opinion that the industry could help a great deal in research settings.4 The CTSA program would also this area by providing funds for faculty and staff, as seem to reward sites for developing and using this well as lending schools the expertise of industrial sci- discipline, although there is still a steep educational entists. Through such efforts, pharmacometrics can curve. As a bridging discipline, academic success for indeed mature and grow as a scientific discipline. the pharmacometrician implies that one is a member There continues to be belief by some that, amidst of an institution with established expertise in at least financial uncertainty, corporate executives will be some of the related disciplines (Figure 1). This is true less likely to invest in “soft sciences” with “no mea- for both training and research perspectives, as access surable deliverable.” Hopefully, this is a less pervasive to a diverse student pool is essential, as previously notion now than in the past. Pharmacoeconomic discussed. Funding opportunities would seem to fall data support the use of modeling and simulation into 3 main areas: application development, infor- throughout drug development41 but especially in matics, and translational research where clinical phase II. It is true, however, that expectations of pharmacology is already a recognized discipline. The some senior managers do not necessarily align with successful academic pharmacometrician must cer- the learn-confirm paradigm.42 Sometimes the oppor- tainly maintain a diverse research portfolio. As pre- tunity for model-based input into go/no-go decisions viously discussed, industry relationships would is lost because there remains a hope that some of the seem to be essential in this regard as the academician time-consuming and expensive phases of develop- is constantly confronted with the necessity of financ- ment can be skipped. Classically, the stages most ing the research in this area. This will hopefully often skipped were those in which dose finding was change with more publications of academic research the objective. There are social dynamic limitations facilitated by pharmacometrics-driven study designs, that prohibit implementation of pharmacometrics in analysis plans, and research outcomes. all cases, and some financial wishful thinking with respect to staffing is also problematic. These occur CONCLUSION for many other groups in industry as well and contribute to burnout and missed opportunities, not to Pharmacometrics is an interdisciplinary science mention poorly informed development programs. with tremendous potential to influence decision With regard to career satisfaction, much is deter- making through the construction of mathematical mined, not surprisingly, by the research environment. models that define, challenge, and resolve queries There is some aspect of historical success that affects surrounding biological processes. Its application in the ability of industry scientists with pharmacomet- drug development during the past 20 years has led to rics expertise to have impact on drug development the realignment of corporate infrastructures in many decision making. Companies with strong, visionary companies and increased the demand for skilled leadership, particularly if they have demonstrated pharmacometricians. Regulatory authorities have historical successes, perform well and continue to populated their review groups with these scientists attract top talent. Likewise, companies without a as well, further increasing the demand for the skill pedigree in pharmacometrics find it difficult to and, more importantly, creating visible evidence of establish a credible presence, especially if the vision the impact of this discipline on critical thinking for the group or scientist is not facilitated by during drug development. Creative solutions are

644 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS required to provide adequate training resources for 3 What field(s) or discipline(s) constitutes your the future. Our proposal for a global virtual research training/education? faculty will require significant coordination but is not insurmountable given today’s technology. The Business (Marketing/Operations) results from a recent questionnaire polling opinion Pharmacology Medicine on the demand for pharmacometrics expertise and Engineering the satisfaction with existing training resources are Pharmacy provided in the Appendix. This survey provides a Statistics/Biostatistics complementary view from the community of scien- Pharmaceutics tists who call themselves pharmacometricians. 0 5 10 15 20 25 30 35 40 45 % Response

APPENDIX Response, % Response, n Questionnaire Results 0.5 1 1 Please check the box that bestidentifies your 31.8 64 company or institution and please provide its name. 6.0 12 11.4 23 42.8 86 Research Hospital 21.4 43 Academic Institution Consultant 41.8 84 CRO Regulatory Agency Generics Big PhRMA Medium PhRMA 4 What is your highest degree? Small PhRMA 0 5 10 15 20 25 30 35 % Response PhD

PharmD Response, % Response, n MBA 4.4 9 MD 23.7 49 7.3 15 MS

9.2 19 BS 1.0 0 0.0 2 0 10 20 30 40 50 60 70 % Response 31.4 65 16.9 35 6.3 13 Response, % Response, n 68.4 143 2 What is your primary role at your company? 9.1 19 0.5 1 3.8 8 Biostatistics 17.2 36 1.0 2 Clinical Pharmacology

Drug Metabolism & PK

Pharmacometrics 5 Number of years since highest degree attained?

0 10 20 30 40 50 60 % Response Mean 9.47 SD 7.94 Minimum 0 Response, % Response, n Maximum 35 3.1 6 25.5 50 13.3 26 58.2 114

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6 To what extent do you feel your company or 9 How many individuals with pharmacometrics skills institution’s management appreciate the value of are employed at your company or institution? pharmacometrics to advance drug development?

> 10

Substantial appreciation 6 - 10

Adequate appreciation

3 - 5 Not enough

1 - 2 Not at all

0 10 20 30 40 0 10 20 30 40 50 % Response % Response

Response, % Response, n Response, % Response, n

40.4 84 36.7 76 20.2 42 17.4 36 37. 0 77 22.7 47 2.4 5 23.2 48

7 To what extent do you feel your company or institution has invested in pharmacometrics (ie, has 10 Do you/does your company/institution plan to adequate resources) with respect to personnel, hire additional personnel for pharmacometrics positions? environment, and application (usage)?

Yes, > 2 positions

Substantial investment Yes, 1 - 2 positions

Adequate amount Yes, but not presently Not enough

No Not at all

0 5 10 15 20 25 30 35 40 45 0 5 10 15 20 25 30 35 40 45 % Response % Response Response, % Response, n Response, % Response, n 29.5 61 14.2 29 18.4 38 25.5 52 43.0 89 43.1 88 9.2 19 17.2 35

8 Are you confident that the personnel responsible for pharmacometrics in your company/institution are adequately trained and able to convey their results? 11 Of the people you regard as experienced pharmacometricians, where/how do you feel they acquired their knowledge? Completely confident

Sufficient confidence Trained for pharmacometrics

Training in school/experience Not enough

On-the-job experience Not at all

Self-taught 0 5 10 15 20 25 30 35 40 45 % Response 0 10 20 30 40 50 60 % Response

Response, % Response, n Response, % Response, n

25.6 53 32.4 67 43.5 90 56.0 116 26.6 55 43.5 90 4.4 9 28.0 58

646 • J Clin Pharmacol 2008;48:632-649 THE DISCIPLINE OF PHARMACOMETRICS

12 Do you feel the training resources (texts, degree 15 What is your impression of existing pharmacomet- programs, courses, workshops, etc) for pharmacometrics rics-related workshops, courses, mini-symposiums, etc? are currently adequate?

Can’t assess

Can’t assess Worthwhile and productive

Yes Room for improvement

0 5 10 15 20 25 30 35 40 45 No % Response

Response, % Response, n 0 10 20 30 40 50 60 % Response 14.0 29 Response, % Response, n 41.6 86 44.4 92 22.8 47 19.4 40 57.8 119 16 What elements of training are in highest demand for 13 Do you feel that there are adequate educational pharmacometricians? programs for pharmacometrics training?

Can’t assess

Communications Can’t assess Programming

Methodology

Yes Techniques/Applications

Foundation/Concepts

No 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 % Response

0 5 10 15 20 25 30 35 40 45 50 55 60 65 % Response Response, % Response, n

Response, % Response, n 7.2 15 29.8 62 19.7 41 43.8 91 15.9 33 57.7 120 64.4 134 74.0 154 48.6 101 14 What is your experience with pharmacometrics- related workshops, courses, mini-symposiums, etc?

Methods course e.g., Metrum

Meeting short course e.g. AAPS

NONMEM workshops Financial disclosure: Dr Mike Fossler is an employee of GSK

No experience Pharmaceuticals and is a shareholder in the company. Mr Dave Cadieu is the principal of the KDC Group and is the sole shareholder. 0 5 10 15 20 25 30 35 40 45 50 55 Dr Marc Gastonguay is the scientific director and chairman of the % Response board of directors of the Metrum Institute and the president and CEO of the Metrum Research Group. Dr Barrett’s efforts on this work were Response, % Response, n supported in part by NIH/NICHD, Pediatric Pharmacology Research 30.8 64 Unit, Grant # HD037255-06 and NIH/NCRR, Institutional Clinical 12.5 26 and Translational Science Award, NIH1U54 # RR023567-01; 50.5 105 Dr Barrett is on the board of directors of the Metrum Institute. 6.3 13

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