New Drug Approval Probability Model in Phased Clinical Trials
American Journal of Health Research
Volume 1, Issue 3, November 2013, Pages: 81-85
Received: Sep. 30, 2013;
Published: Nov. 20, 2013
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Onyiaorah, I V, Dept. of Histopathology, Faculty of Medicine. Nnamdi Azikiwe University, PMB 5001 Nnewi.Anambra State- Nigeria
Oyeka, ICA, Department of Statistics, NnamdiAzikiwe University, PMB 5025. Awka, Anambra State- Nigeria
Efobi, CC, Dept of Haematology & Oncology University of Port-Harcourt, River State Nigeria
Onyiaorah, AA, Dept of Ophthalmology.ESUT Teaching Hospital, Park-Lane GRA Enugu
Okeh, UM, Dept of Industrial Mathematics and Applied Statistics, Ebonyi State University Abakaliki, Nigeria
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Modern medicine brought with it “evidence-based practice”, which demands that a diagnostic test or treatment method or drug to be used on humans must be proven to be at least safe and efficacious; and the result from the use of such must be reliable and repeatable. These days, the need for evidence-based practice has become even more imperative. Evidence-based practice extends to veterinary practice and also to non-medical practices, for instance in oil exploration. To satisfy these demands in drug testing, robust statistical methods of assessment and ethical procedure must be employed. We here develop and present a probability model for the approval of a new drug intended for use in man or animal. The model showed that there should be more than one evaluation committee working on the approval of one drug at a time. This approach would help in minimizing the error of approving wrongly drugs that should never have been approved. The proposed method has proven the workability and value of using at least three independent evaluation committees, working with the same sets of criteria, in assessing the basis for the use of a new drug and its approval.
Evaluation Committee, Approval Probability, Clinical Trial, New Drugs, Informed Consent
To cite this article
Onyiaorah, I V,
New Drug Approval Probability Model in Phased Clinical Trials, American Journal of Health Research.
Vol. 1, No. 3,
2013, pp. 81-85.
Rising K, Bacchetti P, Bero L (2009).Reporting Bias in Drug Trials Submitted to the Food and Drug Administration: Review of Publication and Presentation: PLOS Medicine.http://www.biomedcentral.com/1471-244X/8/3
Gobburu J. V. S and Lesko L. J (2009).Quantitative Disease, Drug, and Trial Models.Annual Review of Pharmacology and Toxicology. 49: 291-301.
Chow S.C. and Liu J.P( 2004). Design and Analysis of Clinical Trials: Concept and Methodologies.John Willey and Sons.
Huff T. E (2003). The Rise of Early Modern Science: Islam, China, and the West.
Lipkovich I, Adams D H, Mallinckrodt C. Faries D, Baron D., and Houston J. P (2008). Evaluating Dose Response from flexible Dose Clinical Trials.BMC Psychiatry.
Pocock S. J (2004). Clinical Trials. A Practical Approach. John Wiley & Sons.
Gebski V. Beller E, Keech A. C (2001) Randomized Trials: Elements of a Good Study. Medical Journal of Australia. 175: 272-274. Cambridge University Press. p. 218
Koren G, Boloja M, Long D, Feldman Y, Shear N. H (1998) Perception of teratogenic risk by pregnant women exposed to drugs and chemicals during the first trimester. Am J Obstet Gynecol. 160:1190-4.
Dally, A. Thalidomide (1998). Was the tragedy preventable? Lancet.351:1197-1199
Koren G. Pastuszak A (1990). Prevention of unnecessary pregnancy termination by counselling women on drug, chemical and radiation exposure during the first trimester. Teratology. 41:657-61.
Koren G, Pastuszak A, Sinya I (1998). Drugs in pregnancy. N Engl J Med. 338(16):1128-1137.
Collier R. (2009)Drug development cost estimates hard to swallow. CMAJ. February 3; 180(3): 279–280