The use of computer modeling to simulate randomized control trials as a means to lower pharmaceutical costs



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THE USE OF COMPUTER MODELING TO SIMULATE RANDOMIZED CONTROL TRIALS AS A MEANS TO LOWER PHARMACEUTICAL COSTS

by

Terence Chen

BA, Cell Biology and Neuroscience, Political Science, Rutgers University, 2010

Submitted to the Graduate Faculty of

the Department of Health Policy and Management

Graduate School of Public Health in partial fulfillment

of the requirements for the degree of

Master of Public Health

University of Pittsburgh
2013





UNIVERSITY OF PITTSBURGH

GRADUATE SCHOOL OF PUBLIC HEALTH

This essay is submitted
by
Terence Chen
on
April 26, 2013
and approved by
Essay Advisor:

Mark S. Roberts, MD, MPP _________________________________

Professor and Chair of Health Policy and Management

Health Policy and Management

Graduate School of Public Health

University of Pittsburgh


Essay Reader:

Janice C. Zgibor, RPh, PhD ________________________________

Assistant Professor of Epidemiology

Epidemiology

Graduate School of Public Health

University of Pittsburgh




Copyright © by Terence Chen

2013

ABSTRACT

T


Mark S. Roberts, MD, MPP
THE USE OF COMPUTER MODELING TO SIMULATE RANDOMIZED CONTROL TRIALS AS A MEANS TO LOWER PHARMACEUTICAL COSTS

Terence Chen, MPH

University of Pittsburgh, 2013

he cost to develop new drugs has been steadily rising in the past 30 years. It is estimated in 2005 that the average cost to develop one new drug is $1.3 billion dollars. This amount of money is a significant cost borne by pharmaceutical companies which is then passed down in the healthcare system. However, this significant cost borne by pharmaceutical companies leads to decreased innovation and risk because of the need to successfully put the drug to market. To be more specific, a significant contributor to the astronomical cost of the development of new drugs is Phase III testing in clinical trials. This paper explores the possibility of using a validated computer model such as Archimedes to simulate the control group of a Phase III trial in order to decrease costs. In addition, the computer model could help predict differences in the trial groups. In allowing validated computer models to lower the cost of Phase III clinical trials, pharmaceutical companies can be more aggressive in their solutions, developing drugs at a cheaper cost and provide faster innovation. In addition, computer modeling can streamline the clinical trial process, increasing efficiency of drug testing and ultimate providing for a better healthcare system. This increase in efficiency would carry over into public health due to lowered cost and potentially more effective drugs in the marketplace.


TABLE OF CONTENTS


TABLE OF CONTENTS v

List of tables vi

List of figures vii

1.0 Introduction 1

2.0 Background to clinical drug testing 4

3.0 The archimedes model 6

4.0 validation of the archimedes model 10



1.0 the potential use of archimedes in clinical trials 15

2.0 Conclusion 20

bibliography 21

bibliography 21

List of tables


Table 1. Changes in Clinical Trials: Resources, Length, and Participation………………............2

Table 2. Types of Clinical Trials………………………………………………………….............4

Table 3. Results of Hypothetical Clinical Trials………………………………………...............18

List of figures


Figure 1. Average cost to develop a new drug……………………………………………............1

Figure 2. Comparison of model and trial: fraction of patients having myocardial infarctions in UKPDS .........................................................................................................................…............12

Figure 3. Projected savings using Archimedes to supplement Phase III trials………….............17


  1. Introduction

The randomized control trial has long been held as the gold standard in the scientific community when testing hypotheses. In medicine, when introducing new drugs, this remains the standard to which the medical community holds drugs to. However, randomized control trials pose an incredible expense in terms of research cost and liability. This expense leads to increased developmental costs and more costs incurred further down the healthcare chain.


          The rise in research and development costs with regard to new drugs is staggering. From 1975 to 2005, the cost rose from 100 million dollars to over ten times that amount to 1.3 billion dollars1.



Figure 1. Average cost to develop a new drug
Much of the costs incurred from research and development come in the clinical trials of the drug, namely Phase III. Some major cost drivers in Phase III are the length and complexity of the trials themselves. In a span of six years, from 1999 to 2005, the average length of a clinical trial in phase III increase by 70%2. In addition to that significant increase in length, there are other significant increases in cost drivers. In terms of complexity of the trials, the average number of routine procedures per trial increased by 65% and the clinical work staff had its work burden increased by 67%. In addition to these increased cost drivers, the increased recruitment barriers and more stringent test protocols have led to 21% fewer volunteers and 30% less enrollees finishing the entire course of the trial3.

Table 1. Changes in Clinical Trials: Resources, Length, and Participation


The Food and Drug Administration (FDA), the agency in charge of drug testing, is well aware of rising costs of clinical trials. In an effort to stem the tide of these rising costs, the FDA has tried to implement new policies. These policies include allowing remote monitoring of Phase II clinical trials as well as computer modeling in device trials. However, while the purpose of these policies is to reduce the cost of clinical trials, there have not been significant returns. This paper proposes to use an advanced computer model such as Archimedes to be used in Phase III drug testing. Archimedes can serve to model populations, but ultimately, the goal is to use Archimedes to model the control group in Phase III testing to serve as a key component in reducing the cost of clinical trials.

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