Reduction of Controls in Preclinical Clamp Studies using a Nonlinear Mixed-Effects Model

Dette speciale undersøger hvor mange kontroldyr der kræves, hvis historisk information fra tidligere forsøg anvendes. Først præsenteres en ikke-lineær logistisk kurve for dosis-respons forholdet, der benyttes som fundament for forskellige modelleringstilgange. Efterfølgende bruges denne til at analysere to udvalgte historiske forsøg med fokus på resultaterne for den relative styrke af teststo et (en insulin analog) i forhold til kontrolsto et (human insulin). Her inkluderes kun data fra det aktuelle forsøg for at klargøre hvordan forsøgene normalt analyseres, den såkaldte normale tilgang, hvorefter vi fortsætter med at konstruere en varianskomponentmodel kun for human insulin, hvor det undersøges omhyggeligt hvilke faste og tilfældige e ekter samt hvilke transformationer, der skal inkluderes. Derefter konstateres det, at resultaterne ikke ændrer sig sønderligt når analogerne inkorporeres i mod- ellen, og for de to udvalgte dybdegående analyserede analoger, erfares det, at den normale tilgang samt varianskomponenttilgangen giver enslydende resultater for den relative styrke. Dog falder standardafvigelsen for denne parameter i forhold til den normale metode, og disse resultater udfordres yderligere i et simula- tionseksperiment. Dette eksperiment viser generelt at ved at inkludere historisk information i form af den foreslåede varianskomponentmodel, er vi i stand til at fjerne mindst 50% af kontrol rotterne i hvert af forsøgene undersøgt i dybden for at opnå samme niveau af usikkerhed på den relative styrke som i den normale metode. Efterfølgende konstateres det, at dette er i overensstemmelse med det præsenterede teoretiske fundament, ud fra hvilket vi beregner en eksplicit reduktion i antallet af kontrolrotter på henholdsvis 61.8% og 52.5% for to af de historiske forsøg. Endelig diskuteres muligheden for at inkorporere tidligere information vha. en varianskomponentmodel, hvor både en metatilgang såvel som en Bayesiansk tilgang efterprøves. Ovenstående konklu
This thesis examines how many control animals are really needed if we make use of historical information on past studies. First, a nonlinear logistic curve for the dose-response relationship is presented, and used as the foundation for the di erent modelling approaches. Then it is applied to two chosen historical studies with a focus on the results of the relative potency of the test drug under investigation (an insulin analogue) compared to the control drug, human insulin. Here we include data only from the study under investigation to clarify how the studies are normally analysed, the so-called common way, whereupon we continue by building a mixed-e ects model only for human insulin, investigating thoroughly which fixed and random e ects as well as di erent transformations to include. Next, we find that the results do not change dramatically when incorporating the analogues in the model, and for the two chosen analogues analysed in depth, we find that the common and mixed-e ects analysis yield similar results for the estimate of the relative potency. However, the standard errors for these decrease noticeably compared to the benchmark results from the common method, and these results are challenged further in a simulation experiment. This experiment suggests overall that by including historical information in the form of the mixed-e ects model proposed, we are able to remove at least 50% of the control rats in each of the studies looked closely upon to get the same level of uncertainty on the relative potency as in the common analysis. Thereafter, we find that this is in compliance with the theoretical foundation presented, from which we calculate an explicit reduction in the number of control rats of 61.8% and 52.5% respectively for two of the studies. Ultimately, how to incorporate the past information in the form of the mixed-e ects model is discussed, where both a meta approach as well as a Bayesian approach are suggested. The above conclusions are foun