Y OUNG I NNOVATORS 2011 Improving Patient Pharmacotherapy via Informative Study Design and Model-based, Decision Support Jeffrey S. Barrett, PhD, FCP The

YOUNG INNOVATORS 2011

Improving Patient Pharmacotherapy via Informative Study Design and Model-based,

Decision Support

Jeffrey S. Barrett, PhD, FCP

The Children’s Hospital of Philadelphia

University of Pennsylvania School of Medicine

Young Innovators 2011

ABSTRACT• Post approval clinical experience is often essential for evolving

optimal pharmacotherapeutic strategies particularly for patient subpopulations including pediatrics and critically ill patients.

• Clinical pharmacology studies in these "at risk" populations provide targeted investigation focused on evaluating the therapeutic window.

• Much of my research has focused on designing such trials and the evaluation of PK and PK/PD in order to propose dosing recommendations from such studies.

• These studies can improve our understanding of disease biology and many cases these efforts culminate in changes to the standard of care.


ABSTRACT• An important element of this research is the dissemination of

the knowledge that these investigations provide to the caregiver community that ultimately prescribe and manage these patients.

• Decision support systems integrated to a hospital’s electronic medical records system can provide this knowledge real-time in an manner that evolves with the science and the data.

• An emerging consortium of clinical pharmacology, IT and pharmacometric expertise has taken up the task to build such systems to pave the way for expert pharmacotherapy systems in the future.


INTRODUCTION

• Our knowledge regarding the optimal management of drug therapy evolves with time

Pre-IND IND Phase I

Phase II

Phase III

Drug Development Post Marketing EvaluationClinical Practice / Utilization

• Disease biology• Mechanism of action• Basic ADME • PK/PD in healthy

volunteers and patients• Therapeutic window• Safety and efficacy in

target populations

• Special populations• Patient “extremes”• ADR reporting• Long term safety and

efficacy in target populations

• Health economics

• DDI potential• Safety “signals” in patient

subpopulations• Compliance factors• Lifestyle factors• Patient factors

. . . Sometimes, we don’t know what we should know at a particular phase


INTRODUCTION

Well-designed trials . . . • Fulfill study objectives• Are well-powered and designed• Collect meaningful data at the

clinically-relevant occasions• Evaluate clinically-relevant

dose(s) / regimen(s)• Minimize or eliminate sources

of confounding• Study the appropriate

populations / characteristics

Modeling and simulation techniques can facilitate well-designed trials . . .


INTRODUCTIONOUTPUTS FROM MODELING & SIMULATION RESEARCH

• Models to evaluate dose-exposure (PK), exposure-response (PD), clinical outcomes (CTS)

• Model diagnostics and other means of evaluating model appropriateness and generalizability

• Simulations that describe model precision and evaluate parameter sensitivity

• Simulations that test scenarios under which a clinical trial can be conducted (design, dose, sampling scheme, population, etc)

• Forecasting of future events based on progression of model inputs or alteration of experimental conditions

• Feedback loops that update models based on predefined requirements (decision logic)

• Graphical representations of model outputs or performance

http://clincancerres.aacrjournals.org/content/15/1/346/F2.large.jpg


INTRODUCTION

Application of M&S spans many settings that facilitate pharmacotherapy guidance• Systems biology modeling (target

identification and mechanism of action)• Animal disease model to clinic bridge• Formulation development (IVIVC)• Special population modeling (bridging)• Disease progression modeling


3 CASE STUDIES FROM BARRETT LAB

• Actinomycin / Vincristine in children with Cancer

• Fluconazole dosing in Neonates• Pediatric Knowledgebase (PKB)


AMD /VCR IN CHILDREN WITH CANCER

• Old chemotherapeutic agents used in a variety of pediatric cancers without informative dosing guidance

• Drugs often given in combination; difficult to do PK in children with cancer – additionally, venapuncture dissuades parents / children

• BPCA Contract proposed by NIH/NCI– In August of 2002, the Children’s Oncology Group

suspended 3 active protocols for paediatric rhabdomyosarcoma after 4 AMD-associated deaths from VOD


AMD /VCR IN CHILDREN WITH CANCER

Project 1Retrospective StudyPooled historical data from Wilms tumour and RMS studies to define

dose-toxicity relationships

Project 2Catheter Study

Dosing and PK sampling procedure utilizing a single central venous

catheter

Project 3M & S Study

PK/PD models based on exposure-response relationships that

incorporate physiologic-based and mechanistic expression; CTS

Project 4Prospective Study

PK/PD/Out come trial in children with cancer


AMD /VCR IN CHILDREN WITH CANCERRESULTS – PROJECT 1

< 1 y group at greater risk for hepatotoxicity with AMD

Older children at greater risk for neurotoxicity with VCR

Langholz B, Skolnik J, Barrett JS, Renbarger J, Seibel N, Zajicek A, Arndt C. Dactinomycin and vincristine toxicity in the treatment of childhood cancer: A retrospective study from the Children’s Oncology Group. Pediatric Blood & Cancer 57(2):252-7, 2011.



Mimic of in vivo setting– Common catheter configurations– Procedures, agents and conditions for

clearing

1. Cook® 5 french 27 cm catheter fragment

2. 200 µL pipette tip

3. Cook® catheter syringe connector

4. Medex 3-way stopcock

5. 5 mL syringe for waste collection

6. 3 mL syringe for sample collection

Skolnik JM, Zhang AY, Barrett JS, and Adamson PC. Approaches to clear residual chemotherapeutics from indwelling catheters in children with cancer J. Ther. Drug Monitoring 32(6): 741-8, 2010.



Parameter Assumptions/Initial EsitmatesF2: F unbound to central 0.76F5: F bound in catheter 0.24Fbound: F dissociated from bound 1.00Kno: dissociation rate from bound 0.781 hr-1

Krinse: dissociation rate with “pull-push” 1.67 hr-1

K52 = Kno + Krinse*CYCL

Zhang AY, Skolnik JM, Dombrowsky E, Patel D, Barrett JS. Modeling and Simulation Approaches to Evaluate Chemotherapeutics Contamination From Central Venous Catheters in Pediatric Pharmacokinetic Studies (Submitted, Cancer Chemother Pharmacol)



12 kg Dog: 0.03 mg/kg (360 g)AMD

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Pediatric Exposure Profiles following 1.5 mg/m2 AMD

80 KG40 KG20 KG10 KG

Simulated Weight Ranges(10th and 90th Percentiles)

Barrett JS, Gupta M, Mondick JT. Model-based Drug Development for Oncology Agents. Expert Opinion on Drug Discovery 2(2): 185-209, 2007.



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Pop-PK model developed in 34 children with cancer

Model used to verify sample size, sampling scheme and dosing rules

Mondick JT, Gibiansky L, Gastonguay MR, Skolnik J, Veal GJ, Boddy A, Adamson PC, Barrett JS. Population Pharmacokinetics of Actinomycin-D in Children and Young Adults. J Clin Pharmacol: 48(1): 35-42, 2008



• ADVL06B1, A Pharmacokinetic-Pharmacodynamic-Pharmacogenetic Study of Actinomycin-D and Vincristine in Children with Cancer Study officially closed to enrollment on October 5, 2011

• Follow-up ongoing

• PGx complete

• Data assembly ongoing

• Preliminary data analysis ongoing


FLUCONAZOLE DOSING IN NEONATES

• We know . . .– Triazole class, inhibitor of fungal P450 – Excellent CSF, lung, kidney & tissue penetration – Active drug eliminated by kidney with minimal metabolism– Low incidence of adverse events in children/adults– Effective in adults and children– C. albicans & parapsilosis sensitive to Fluconazole– C. galbrata & krusei are uniformly resistant

• We need to know . . .– Pharmacokinetics in infants– Optimal Doses for effective treatment and prevention of emergence of resistance– For systemic treatment: FL (AUC)/ Candida MIC>50– For prevention: no known target– Safety and efficacy


FLUCONAZOLE DOSING IN NEONATESHISTORICAL DATA

PK 6mg/kg

Wiest 1991

H Saxen, K Hoppu1993

Wenzl 1998

Infants

28wkPNA 40d

N=1

26-29 wk PNA d1

N=7

26-29 wk PNA d6

N=7

26-29 wk PNA

d13 N=4

25-29 wkPNA

>30d N=3

Cl (L/hr/kg)

0.0198 0.0108 0.0198 0.03128 0.029

Vd (L/kg) 1.2 1.18 1.84 2.25 1.43

T ½ (hr) 37.4 88.6 67.5 55.2 35

Delayed CL improves with postnatal ageLong t½Large variability in individual PK parametersNo Pharmacokinetic data < 750 gInadequate to support dosing


FLUCONAZOLE DOSING IN NEONATESOBJECTIVES

• To conduct a prospective PK trial to establish a population PK model of fluconazole disposition in infants 23-40 weeks gestation and < 120 days old

• To facilitate PK trial by leveraging clinical practice

– Fluconazole exposure as routine clinical care– Sparse microvolume blood sampling timed with

clinical care– Scavenge left over plasma from discarded

hematology samples to increase samples in PK dataset

• To determine dosage guidelines that provide adequate exposure for treatment and prevention of invasive candidiasis


FLUCONAZOLE DOSING IN NEONATESRESULTS

• Prospective, open label PK trial• Inclusion Criteria

• Infants receiving Fluconazole as routine care• GA 23-40 weeks, PNA<120 days

• Informed consent • Dose and length of therapy determined by clinician• Enrollment stratified by GA & PNA (8 groups)• Clinical information collected from medical record

• Sparse sampling scheme• Up to 6 samples around single dose• Up to 3 samples at steady state (day 7, 14, 21)• Supplement with scavenged samples

• New, highly sensitive LC/MSMS assay (10ng/ml)• Population PK model: Non-linear mixed effect modeling



Characteristics (N=55 infants) Median (Range)

GA at birth (wk) 26 (23-40)

Post-natal Age (days) 16 (1-88)

Weight (g) 1020 (451-7125)

Gender (% male) 56% male

Indication # Infants (%)

Prophylaxis from birth 23 (42 %)

Prophylaxis for broad antibiotic exposure

11 (20 %)

Prophylaxis for NEC 8 (15 %)

Treatment Fungal Sepsis 7 (13 %)

Empiric Treatment Fungal 4 (7 %)

Treatment of + fungal urine 2 (3 %) 1st 2nd 3rd 4th 5th 6th >7th0

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PK dataset•55 infants •357 PK samples

• 217 (61%) timed samples • 140 (39%) scavenged



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Wade KC, Wu D, Kaufman DA, Ward RM, Benjamin DK, Ramey N, Jayaraman B, Kalle H, Adamson PC, Gastonguay M, Barrett JS. Population Pharmacokinetics of Fluconazole in Young Infants. Antimicrob Agents Chemother 52(11):4043-9, 2008.



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Equivalent to 50 mg/kg/day adult<10% infants maintain [Fluc] > MIC 4

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PEDIATRIC KNOWLEDGEBASE• Global appreciation and demand for

personalized medicine• More quantitative data on benefit:risk of

drug therapy exists today with greater appreciation for complexities of dosing requirements• Medication errors and adverse drug reactions affect at least 1.5 million people every year at a cost to the healthcare system between $77 and $177 billion annually • 75% of drugs on market have no information on how to manage drug therapy in children


PEDIATRIC KNOWLEDGEBASE

• Data provided in compendial sources is often based on small studies – many pediatric subpopulations are left behind• Children are dosed (experimented on) every day with the caregiver using only their “best medical judgment” to guide them • The knowledge is static not specific to the patient and does not evolve



ELECTRONIC

RECORDS

M E D I C A L

Direct Indicators of Health Status (vital signs, BP, Temp, HR…)

Disease/Condition specific assessments (Scans, Tests…)

TDM Data (Drug/Biomarker levels)

Clinical Observations & Patient Response to Therapy

Procedures or Interventions


Opportunities for: - Disease progression - Population analysis - Meta analyses . . . correlation

Longitudinal: within patient

Data Mining: across patients


Compendial guidance and other relevant views

of static data

Historical Views of “Like”

Patients

Views to clinically-relevant indicators of pharmacotherapy status and guidance

Views to past patient hospital

visits

Forecasting Tools for Guidance on:· Existing dosing

practices· Caregiver

requested guidance· Projection of

outcomes associated with current or modified care

Dashboard Concept

Views to formulary guidance


• Service-oriented architecture

• Compliant with HL7 CDA

PEDIATRIC KNOWLEDGEBASETHE METHOTREXATE DASHBOARD

•Anti-folate chemotherapeutic agent

•Renal excretion

•Enterohepatic recirculation

•Toxicity at high or prolonged low exposure


Disease Dose Route Leucovorin

ALL 8-15 mg IT No

ALL 20 mg/m2 PO No

ALL 100-300 mg/m2 IV No

NHL 1 g/m2 IV Yes

OS 12 g/m2 IV Yes

Dos e Infus ion (h) N Tim e (h) M TX (uM ) Referenc e

48 0.5 Tatters all 197572 0.5

24 50 Is ac off 197648 0.5

50 - 250 m g/k g 6 78 48 0.9 S toller 197724 10 Nirenberg 197748 1

72 0.1

50 - 350 m g/k g 6 40 48 1 P erez 1978100 - 300 m g/k g 6 33 48 1 E tc ubanas 19780.725 - 15 g/m 2 6 30 24 5 E vans 1979

6 - 8.5 g/m 2 4 to 6 22 48 1 Junk a 197972 0.2 A bels on 198396 0.075

8 g/m 2 4 96

7.5 g/m 2 6 12

1 - 15 g/m 2 bolus or 20 42

50 - 250 m g/k g 4 46


METHOTREXATE SHOULD BE USED ONLY BY PHYSICIANS WHOSE KNOWLEDGE AND EXPERIENCE INCLUDE THE USE OF ANTIMETABOLITE THERAPY. BECAUSE OF THE POSSIBILITY OF SERIOUS TOXIC REACTIONS (WHICH CAN BE FATAL): • METHOTREXATE SHOULD BE USED ONLY IN LIFE THREATENING

NEOPLASTIC DISEASES, OR IN PATIENTS WITH PSORIASIS OR RHEUMATOID ARTHRITIS WITH SEVERE, RECALCITRANT, DISABLING DISEASE WHICH IS NOT ADEQUATELY RESPONSIVE TO OTHER FORMS OF THERAPY.

• DEATHS HAVE BEEN REPORTED WITH THE USE OF METHOTREXATE IN THE TREATMENT OF MALIGNANCY, PSORIASIS, AND RHEUMATOID ARTHRITIS.

• PATIENTS SHOULD BE CLOSELY MONITORED FOR BONE MARROW, LIVER, LUNG AND KIDNEY TOXICITIES. (See PRECAUTIONS.)

• PATIENTS SHOULD BE INFORMED BY THEIR PHYSICIAN OF THE RISKS INVOLVED AND BE UNDER A PHYSICIAN'S CARE THROUGHOUT THERAPY.

BLACK BOX WARNING


Current procedure is to photocopy “master” nomogram for specific protocols and hand plot individual data


MTX Cleared• MTX level ≤ 0.1 µM• Patient can be

discharged

0 – 24 Hours

Continuing Hydration

• D5 0.22% NaCl with 40 mEq/L NaHCO3 at 100 ml/m2/hr

• Urine pH measured every 8h. If pH < 7, 10 ml/kg hydration fluid is given over 30 min and pH measured

• Lasts until MTX level ≤ 0.1 µM

Before Administration

Prehydration• 750 ml/m2 of D5 0.22%

NaCl with 40 mEq/L NaHCO3 is given over 1 hour

• If urine pH < 7, 0.5 mEq/L NaHCO3 is given over 30 minutes. Repeated if urine pH is < 7 after 1 hour

LVR Administration

• LVR starts 24 - 42 h after start of MTX infusion as 15 mg/m2 IVSS over 15 minutes, every 6 hours

• Dose can be modified based on protocol-specific nomogram because of excretion delay

• Lasts until MTX level ≤ 0.1 µM

MTX Administration

• Urine pH must be ≥ 7• 25 mg/ml solution in

Dextrose 5% in water (D5W)

• Maximum absolute dose: 20g

MTX TDM• Begins 24 hours after

the start of MTX infusion

• Results plotted on protocol-specific nomogram

• Continues daily until MTX level ≤ 0.1 µM

24 Hours - Discharge





PEDIATRIC KNOWLEDGEBASEVISION

An international consortium of pediatric centers of excellence that support and drive the development of the PKB

PKB-lite development for clinics, institutions without EMRs and small physician offices

Global connectivity that accommodates regional and global best practices with guidance options

Guidance for developing countries / institutions


DISCUSSION• Modeling and simulation activities

allow the investigator to:• Select the right dose or dose

range• Use the minimal, but most informative, sampling scheme to produce meaningful results that satisfy regulatory requirements• Propose a design / population that has the greatest likelihood of fulfilling study objectives.


DISCUSSION• The link between clinical

pharmacology and medical informatics will provide an excellent form for “real” personalized medicine:• Decision support systems which

integrate patient records with drug and disease-specific indices.

• Disease progression with forecasting of individual patient disease trajectories based on treatment modality options.


ONGOING RESEARCH IN BARRETT LAB

• Disease progression modeling in pancreatic cancer• Model-based approaches to study nanomedicine strategies in oncology• Disease progression modeling in Spinal Muscular Atrophy (SMA)• Translational research in Neuro AIDS• Clinical evaluation of NK1r antagonism in NeuroAIDS• PK/PD relationships for next generation COX-2 inhibitors• PK/PD for natural products (frankinsense, silymarin, etc)• Model-based strategies for Traditional Chinese Medicine (TCM)• Clinical trial design optimization for early phase drug development in oncology

(NCI/CTEP)• PBPK strategies in children to guide hospital-based dosing in critically-ill children• PK/PD relationships in obese children• Correlation of DDI potential and observed toxicity in children with cancer


ACKNOWLEDGMENTS

LAPK/PD Staff (past and present)• Di Wu, PhD• Dimple Patel, MS• Erin Dombrowsky, MS• Sarapee Hirankarn, PhD• Chee Ng, PhD• Yin Zhang, PharmD, PhD• Manish Gupta, PhD• Divya Menon, PhD• Doug Marsteller, PhD• Jason Williams, PhD• James Lee, PhD• Ganesh Moorthy, PhD• Gaurav Bajaj, PhD• Vu Nguyen, BS• Mahesh Narayan, MS• John Mondick, PhD• Craig Comisar, PhD• Sarah Kurliand, MBA• Linda Pederson, MBA• Heng Shi, PhD• Bhuvana Jayaraman, MS• Sundarajaran Vijakumar, PhD• Kalpana Vijakumar, MS

Collaborators• Stephen Douglas, MD• Peter C Adamson, MD• Carolyn Felix, MD• Athena Zuppa, MD• Jeffrey Skolnik, MD• Kelly Wade, MD• Walter Kraft, MD• John van den Anker, MD• Mike Fossler, PharmD, PhD• Marc Gastonguay, PhD• Sander Vinks, PhD• Andrea Edginton, PhD• Ram Agharkar, PhD• Shashank Rohatagi, PhD• Jun Shi, MD• Bernd Meibohm, PhD• Stephanie Laer, PhD• Hong Yuan, MD• Olivera Marsenic, MD• Hartmut Derendorf, PhD• Gunther Hochhaus, PhD• Toshimi Kimura, PhD• Jamie Renbarger, MD• Pat Thompson, MD

• Carsten Skarke, MD• Nick Holford, MD• Brian Anderson, MD• Saskia DeWildt, MD• Leslie Mitchell, PhD• Guy Young, MD• Leslie Ruffino, MD• Garret Fitzgerald, MD• Dwight Evans, MD• Dave Flockhart, MD• Robert Gross, MD• Brian Strom, MD• Dave Cadieu, BS• Diva Deleon, MD• Richard Aplenc, MD• Scott Shulman, MD• Greg Hammer, MD• David Drover, MD• Anne Zajicek, PharmD, MD• Jane Bai, PhD• Sandeep Dutta, PhD


REFERENCESZuppa AF, Adamson PC, Barrett JS. Letter to the Editor, Pediatric drug labeling: improving the safety and efficacy of pediatric therapies, J Pediatr. Pharmacol Ther 9(1): 70-71, 2004.

Barrett JS, Collison KR. Dosing LMWH in special populations: safety, PK/PD and monitoring considerations. International J of Cardiovascular Med and Science 4(2): 41-54, 2004.

Barrett JS, Labbe L, Pfister M. Application and impact of population pharmacokinetics in the assessment of antiretroviral pharmacotherapy. Clinical Pharmacokinetics 44(6): 591-625, 2005.

Zuppa AF, Mondick J, Davis LA, Maka D, Tsang B, Narayan M, Nicholson C, Patel D, Collison KR, Adamson PC, Barrett JS. Drug Utilization in the Pediatric Intensive Care Unit: Monitoring Prescribing Trends and Establishing Prioritization of Pharmacotherapeutic Evaluation of Critically-ill Children. J. Clin. Pharmacol. 45: 1305-1312, 2005.

Meibohm B, Panetta C, Barrett JS. Population pharmacokinetic studies in pediatrics: Issues in design and analysis. AAPS Journal. 7(2): Article 48: E475-E487, 2005.

Kenna LA, Labbe L, Barrett JS, Pfister M. Modeling and simulation of adherence: Approaches and applications in Therapeutics. AAPS Journal. 7(2): E390-E407, 2005.

Zuppa AF, Nicolson SC, Adamson PC, Wernovsky G, Mondick JT, Burnham N, Hoffman TM, Gaynor WJ, Davis LA, Greeley WJ, Spray TL, Barrett JS. Population Pharmacokinetics of Milrinone in Neonates with Hypoplastic Left Heart Syndrome Undergoing Stage 1 Reconstruction, Anesthesia & Analgesia 102(4):1062-9, 2006.

Barrett JS, Gupta M, Mondick JT. Model-based Drug Development for Oncology Agents. Expert Opinion on Drug Discovery 2(2): 185-209, 2007.

Barrett JS. Facilitating Compound Progression of Antiretroviral Agents via Modeling and Simulation. J Neuroimmune Pharmacol 2:58-71, 2007.

Zuppa AF, Vijayakumar S, Mondick JT, Pavlo P, Jayaraman B, Patel D, Narayan M, Boneva T, Vijayakumar K, Adamson PC, Barrett JS. Design and implementation of a web-based hospital drug utilization system. J Clin Pharmacol: 47(9): 1172-1180, 2007.

Barrett JS. Quantitative Pharmacology in a Translational Research Environment. Chinese J Clin Pharmacol Therapeut: 12(10): 1081-88, 2007.

Skolnik JT, Barrett JS, Jayaraman B, Patel D, Adamson PC. Shortening the Timeline of Pediatric Phase 1 Trials: The Rolling Six Design. J. Clin Oncol 26(2): 190-5, 2008

Barrett JS, Mondick JT, Narayan M, Vijayakumar K, Vijayakumar S. Integration of Modeling and Simulation into Hospital-based Decision Support Systems Guiding Pediatric Pharmacotherapy. BMC Medical Informatics and Decision Making 8:6, 2008.

Barrett JS. Applying Quantitative Pharmacology in an Academic Translational Research Environment. AAPS Journal 10(1):9-14, 2008.

Barrett JS, Jayaraman B, Patel D, Skolnik JM. A SAS-based solution to evaluate study design efficiency of phase I pediatric oncology trials via discrete event simulation. Computer Methods and Programs in Biomedicine 90: 240-250, 2008.

Barrett JS, Fossler MJ, Cadieu, KD and Gastonguay MR. Pharmacometrics, A Multidisciplinary Field to Facilitate Critical Thinking in Drug Development and Translational Research Settings. J Clin. Pharmacol 48(5): 632-49, 2008. Published in Chinese Journal as well Chinese J Clin Pharmacol Ther. 13(5): 481-493, 2008.

Zuppa AF, Barrett JS. Pharmacokinetics and pharmacodynamics in the critically ill child. Pediatr Clin North Am. 55(3):735-55, 2008.

Skolnik JM and Barrett JS. Refining the Phase 1 Pediatric Trial. Pediatric Health 2(2): 105-106, 2008. ponse. J Clin Oncology 29(23):3109-11, 2011.


REFERENCESBarrett JS, Shi J, Xie H, Huang X, Fossler MJ and Sun R. Globalization of Quantitative Pharmacology: First International Symposium of Quantitative Pharmacology in Drug Development and Regulation. J Clin

Pharmacol 48(7): 787-792, 2008.

Barrett JS, Patel D, Jayaraman B, Narayan M, Zuppa A. Key Performance Indicators for the Assessment of Pediatric Pharmacotherapeutic Guidance. J Pediatr Pharmacol Ther 13: 141-155, 2008.

Wade KC, Wu D, Kaufman DA, Ward RM, Benjamin DK, Ramey N, Jayaraman B, Kalle H, Adamson PC, Gastonguay M, Barrett JS. Population Pharmacokinetics of Fluconazole in Young Infants. Antimicrob Agents Chemother 52(11):4043-9, 2008.

Barrett JS, Skolnik JM, Jayaraman B, Patel D, Adamson PC. Improving Study Design and Conduct Efficiency of Event-Driven Clinical Trials via Discrete Event Simulation: Application to Pediatric Oncology. Clinical Pharmacol Ther 84(6): 729-733, 2008.

Menon-Andersen D, Mondick JT, Jayaraman B, Thompson PA, Blaney SM, Adamson PC, Barrett JS. Population Pharmacokinetics of Imatinb Mesylate and its Metabolite in Children and Young Adults. Cancer Chemother and Pharmacol 63(2):229-38, 2009.

Wade KC, Benjamin Jr. DK, Kaufman DA, Ward RM, Smith PB, Jayaraman B, Adamson PC, Gastonguay M, Barrett JS. Fluconazole dosing for the prevention or treatment of invasive candidiasis in young infants. Ped Infectious Disease J 28(8): 717-23, 2009.

Läer S, Barrett JS, and Meibohm B. The In Silico Child: Using Simulation to Guide Pediatric Drug Development and Manage Pediatric Pharmacotherapy. J Clin Pharmacol 49(8): 889-904, 2009.

Su F, Nicolson SC, Gastonguay MR, Barrett JS, Adamson PC, Kang DS, Godinez RI, Zuppa AF. Population Pharmacokinetics of Dexmedetomidine in Infants Following Open Heart Surgery. Anesth Analg. 110(5):1383-92, 2010.

Marsenic O, Zhang L, Zuppa A, Barrett JS, Pfister M. Application of Individualized Bayesian Urea Kinetic Modeling to pediatric hemodialysis. ASAOI J 56(3):246-53, 2010.

Kimura T, Kashiwase S, Makimoto A, Kumagai M, Taga T, Ishida Y, Ida K, Nagatoshi Y, Mugishima H, Kaneko M, Barrett JS. Pharmacokinetic and pharmacodynaminc Investigation of Irinotecan hydrochloride in Pediatric Patients with Recurrent or Progressive Solid Tumors. Int J Clin Pharmacol Ther. 48(5):327-334, 2010.

Skolnik JM, Zhang AY, Barrett JS, and Adamson PC. Approaches to clear residual chemotherapeutics from indwelling catheters in children with cancer J. Ther. Drug Monitoring 32(6): 741-8, 2010.

Langholz B, Skolnik J, Barrett JS, Renbarger J, Seibel N, Zajicek A, Arndt C. Dactinomycin and vincristine toxicity in the treatment of childhood cancer: A retrospective study from the Children’s Oncology Group. Pediatric Blood & Cancer 57(2):252-7, 2011.

Dombrowsky E, Jayaraman B, Narayan M, Barrett JS. Evaluating Performance of a Decision Support System to Improve Methotrexate Pharmacotherapy in Children with Cancer. J. Ther. Drug Monitoring 33(1): 99-107, 2011.

Piper L, Smith B, Hornik CP, Cheifetz IM, Barrett JS, Moorthy G, Wade KC, Cohen-Wolkowiesz, Benjamin DK. Fluconazole Loading Dose Pharmacokinetics and Safety in Infants. Pediatric Infectious Disease J 30(5): 375-8, 2011.

Barrett JS, Zuppa AF, Adamson PC, Patel D and Narayan M. Prescribing Habits and Caregiver Satisfaction with Resources for Dosing Children: Rationale for More Informative Dosing Guidance. BMC Pediatrics 11: 25, 2011.

Maitland ML, Bies RR, Barrett JS. A Time to Keep and a Time to Cast Away Categories of Tumor Response. J Clin Oncology 29(23):3109-11, 2011.


BIOS/CONTACT INFOBiographyDr. Jeffrey S. Barrett, is Research Professor of Pediatrics, University of Pennsylvania School of Medicine, the Director of the Laboratory for Applied PK/PD in the Division of Clinical Pharmacology and Therapeutics at the Children's Hospital of Philadelphia (CHOP) and an Associate Scholar in the Center for Clinical Epidemiology and Biostatistics at The University of Pennsylvania. Dr. Barrett served as the Principal Investigator for CHOP's Pediatric Pharmacology Research Unit and heads the Kinetic Modeling and Simulation core of the Penn/CHOP CTSA. He also manages the pharmacology and biostatistics cores for several multidisciplinary projects both within CHOP, UPenn and various multi-center cooperative groups. He received his BS from Drexel University in Chemical Engineering and his Ph.D. in Pharmaceutics from the University of Michigan. Dr. Barrett spent 13 years in the pharmaceutical industry involved with PK/PD aspects of clinical drug development and was an early proponent of industrial pharmacometrics prior to joining CHOP. He is a Fellow of the American College of Clinical Pharmacology (ACCP) and the American Association of Pharmaceutical Scientists (AAPS) and received the Young Investigator and Clinical Pharmacology Mentorship Awards from ACCP in 2002 and 2007 respectively. He is a member of the FDA Clinical Pharmacology Advisory Committee, the Board of Directors of the Metrum Research Institute and the Scientific Advisory Board of Pharsight Corporation. Dr. Barrett has co-authored over 100 manuscripts, 135 abstracts and has given over 100 invited lectures on PK/PD, clinical pharmacology and pharmacometrics. He joined the Editorial Boards of the Journal of Clinical Pharmacology in 2007 and the Journal of Pharmacokinetics and Pharmacodynamics in 2009. Dr. Barrett has mentored numerous physician fellows and post doctoral candidates in clinical pharmacology and pharmacometrics and continues to evolve his training program to accommodate the demand for training in this area. Dr. Barrett’s research interest is focused on investigating sources of variation in pharmacokinetics and pharmacodynamics applying clinical pharmacologic investigation coupled with modeling and simulation strategies to pursue rational dosing guidance. He develops pharmacometric approaches to advance PK/PD, medical informatics and disease progression modeling. Dr. Barrett has also integrated model-based decision support systems with hospital electronic medical records and pioneered the pediatric knowledgebase development program for the past 6 years. He is actively involved with creating disease progression models for spinal muscular atrophy and pancreatic cancer. His team is developing model-based development approaches for Traditional Chinese Medicine, nanomedicine PK/PD-guided delivery and gene therapy.

Contact Details:Jeffrey S. Barrett, PhD, FCP

Colket Translational Research Building, Rm 4012 Ph: 267-426-5479

3501 Civic Center Blvd Fax: 267-425-0114

Philadelphia, PA 19104 Email: [email protected]

Documents

Y OUNG I NNOVATORS 2011 Improving Patient Pharmacotherapy via Informative Study Design and Model-based, Decision Support Jeffrey S. Barrett, PhD, FCP The