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Preclinical Development: Overview01:28

Preclinical Development: Overview

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Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
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Clinical Trials: Overview01:11

Clinical Trials: Overview

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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Drug Discovery: Overview01:26

Drug Discovery: Overview

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Drug Administration and Therapy Phases: Overview01:26

Drug Administration and Therapy Phases: Overview

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Drugs, the chemical agents used in diagnosing, treating, or preventing diseases, undergo a four-phase process of development: pharmaceutic, pharmacokinetics, pharmacodynamics, and therapeutic.
The pharmaceutical phase focuses on leveraging the physicochemical properties of the drug to design and manufacture an effective product. Variants include orally administered tablets or capsules, topical creams or ointments, and parenteral-delivery solutions or emulsions.
The pharmacokinetic phase...
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In Vitro Drug Release Testing: Overview, Development and Validation01:10

In Vitro Drug Release Testing: Overview, Development and Validation

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In vitro dissolution and drug release tests assess how quickly and how much of a drug is released from its dosage form into an aqueous medium under standardized laboratory conditions. These tests are essential tools in pharmaceutical development and quality assurance, offering insight into the drug's performance before clinical use.During formulation development, dissolution testing identifies incomplete or inconsistent drug release issues. It also supports decisions on selecting the optimal...
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Drug Regulation01:25

Drug Regulation

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Drug regulation encompasses the management of drug usage by evaluating its safety and efficacy through assessments conducted by regulatory authorities. Regrettably, the history of drug regulation is marred by several catastrophic events. One such incident is the Elixir Sulfanilamide tragedy, in which the toxic compound diethyl glycol was included in a sweet-tasting medication, leading to numerous fatalities. This event prompted the enactment of the Food, Drug, and Cosmetic Act in 1938. Under...
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Video Experimental Relacionado

Updated: Jan 7, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

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Desarrollo de Fármacos

Bhargav Teja Nallapu1,2, Tianchen Qian3, Richard B Lipton4

  • 1Technical University of Delft, Delft, Zuid-Holland, Netherlands.

Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 25, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Los modelos predictivos pueden mejorar los ensayos clínicos de la enfermedad de Alzheimer (EA) al identificar a los pacientes con probabilidades de experimentar un deterioro cognitivo. Este enfoque mejora la potencia y la eficiencia de los ensayos, optimizando la detección de tratamientos eficaces.

Palabras clave:
Enfermedad de Alzheimerensayos clínicosmodelos predictivosinscripción enriquecidaajuste pronósticodeterioro cognitivopotencia estadísticaeficienciadesarrollo de fármacosneurociencia

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Área de la Ciencia:

  • Neurociencia; Ensayos Clínicos; Bioestadística

Sus antecedentes:

  • Los ensayos clínicos de la enfermedad de Alzheimer (EA) a menudo carecen de potencia estadística debido a que una proporción significativa de participantes tratados con placebo no presenta deterioro cognitivo.; La inscripción de participantes con predicción de deterioro en placebo podría mejorar la potencia de los ensayos de tratamiento de la EA.

Objetivo del estudio:

  • Desarrollar y evaluar clasificadores de aprendizaje automático para predecir el deterioro cognitivo clínicamente significativo (DCC) en pacientes con EA.; Evaluar el impacto de las estrategias de inscripción enriquecida y ajuste pronóstico en el diseño y la potencia de los ensayos clínicos de la enfermedad de Alzheimer.

Principales métodos:

  • Se desarrollaron clasificadores de aprendizaje automático utilizando datos demográficos, neuropsicológicos y de biomarcadores de 1072 participantes del ensayo EXPEDITION3 (brazo de placebo).; Se utilizaron simulaciones de plasmodos para comparar la inscripción estándar con dos enfoques novedosos: Inscripción Enriquecida y Ajuste Pronóstico.; Se analizaron los efectos del tratamiento utilizando regresión lineal, con y sin ajustes pronósticos, en ensayos simulados.

Principales resultados:

  • Se observó un deterioro cognitivo clínicamente significativo (DCC) en el 55,8% de los participantes tratados con placebo.; La inscripción enriquecida demostró una mayor potencia estadística en comparación con la inscripción estándar para tamaños de efecto de 0,3 a 0,5.; El ajuste pronóstico redujo el tamaño de muestra requerido para una potencia del 80%, necesitando, por ejemplo, 292 participantes frente a 336 para un tamaño de efecto de 0,3.

Conclusiones:

  • Los modelos predictivos pueden optimizar el diseño de ensayos de EA al identificar a los participantes con probabilidades de experimentar deterioro cognitivo.; La inscripción enriquecida y el ajuste pronóstico son estrategias efectivas para mejorar la potencia y la eficiencia de los ensayos clínicos de la enfermedad de Alzheimer.