RESUMEN
AIM: To quantify the utility of a terminal-phase adjusted area under the concentration curve method in increasing the probability of a correct and conclusive outcome of a bioequivalence (BE) trial for highly variable drugs when clearance (CL) varies more than the volume of distribution (V). METHODS: Data from a large population of subjects were generated with variability in CL and V, and used to simulate a two-period, two-sequence crossover BE trial. The 90% confidence interval for formulation comparison was determined following BE assessment using the area under the concentration curve (AUC) ratio test, and the proposed terminal-phase adjusted AUC ratio test. An outcome of bioequivalent, nonbioequivalent or inconclusive was then assigned according to predefined BE limits. RESULTS: When CL varied more than V, the proposed approach enhanced the probability of correctly assigning bioequivalent or nonbioequivalent and reduced the risk of an inconclusive trial. For a hypothetical drug with between-subject variability of 35% for CL and 10% for V, when the true test-reference ratio of bioavailability was 1.15, a crossover study of n = 14 subjects analysed by the proposed method would have 80% or 20% probability of claiming bioequivalent or nonbioequivalent, compared to 22%, 46% or 32% probability of claiming bioequivalent, nonbioequivalent or inconclusive using the standard AUC ratio test. CONCLUSIONS: The terminal-phase adjusted AUC ratio test represents a simple and readily applicable approach to enhance the BE assessment of drug products when CL varies more than V.
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Proyectos de Investigación , Área Bajo la Curva , Disponibilidad Biológica , Estudios Cruzados , Humanos , Comprimidos , Equivalencia TerapéuticaRESUMEN
Further optimization of the biaryl amide series via extensively exploring structure-activity relationships resulted in potent and subtype selective M(1) agonists exemplified by compounds 9a and 9j with good rat PK properties including CNS penetration. Synthesis, structure-activity relationships, subtype selectivity for M(1) over M(2-5), and DMPK properties of these novel compounds are described.
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Amidas/síntesis química , Amidas/farmacocinética , Hidrocarburos Aromáticos/síntesis química , Hidrocarburos Aromáticos/farmacocinética , Receptor Muscarínico M1/agonistas , Amidas/farmacología , Animales , Barrera Hematoencefálica/metabolismo , Sistema Nervioso Central/metabolismo , Descubrimiento de Drogas , Hidrocarburos Aromáticos/farmacología , Estructura Molecular , Ratas , Relación Estructura-Actividad , Distribución TisularRESUMEN
A series of N-substituted 3-(4-piperidinyl)-1,3-benzoxazolinones and oxindoles are reported which were found to be potent and selective muscarinic M1 agonists. By control of the physicochemical characteristics of the series, particularly the lipophilicity, compounds with good metabolic stability and excellent brain penetration were identified. An exemplar of the series was shown to be pro-cognitive in the novel object recognition rat model of temporal induced memory deficit.
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Benzoxazoles/farmacocinética , Indoles/farmacocinética , Trastornos de la Memoria/tratamiento farmacológico , Agonistas Muscarínicos/farmacocinética , Nootrópicos/farmacocinética , Receptor Muscarínico M1/metabolismo , Animales , Benzoxazoles/química , Benzoxazoles/uso terapéutico , Encéfalo/metabolismo , Indoles/química , Indoles/uso terapéutico , Agonistas Muscarínicos/química , Agonistas Muscarínicos/uso terapéutico , Nootrópicos/química , Nootrópicos/uso terapéutico , Oxindoles , RatasRESUMEN
Introduction: Prediction of human absorption, distribution, metabolism, and excretion (ADME) properties, therapeutic dose and exposure has become an integral part of compound optimization in discovery. Incorporation of drug metabolism and pharmacokinetics into discovery projects has largely tempered historical drug failure due to sub-optimal ADME. In the current era, inadequate safety and efficacy are leading culprits for attrition; both of which are dependent upon drug exposure. Therefore, prediction of human pharmacokinetics (PK) and dose are core components of de-risking strategies in discovery. Areas covered: The authors provide an overview of human dose prediction methods and present a toolbox of PK parameter prediction models with a proposed framework for a consensus approach valid throughout the discovery value chain. Mechanistic considerations and indicators for their application are discussed which may impact the dose prediction approach. Examples are provided to illustrate how implementation of the proposed strategy throughout discovery can assist project progression. Expert opinion: Anticipation of human ADME, therapeutic dose and exposure must be deliberated throughout drug discovery from virtual/initial synthesis where key properties are considered and similar molecules ranked, into development where advanced compounds can be subject to prediction with greater mechanistic understanding and data-driven model selection.