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Minimizar el riesgo polimórfico a través de la exploración computacional y experimental cooperativa

Christopher R Taylor1, Matthew T Mulvee2, Domonkos S Perenyi2

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Resumen
Este resumen es generado por máquina.

La predicción computacional de la estructura cristalina (CSP, por sus siglas en inglés) combinada con experimentos identificó con éxito los polimorfos evasivos de isoniazida e iproniazida, minimizando los riesgos asociados con las formas sólidas farmacéuticas.

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Área de la Ciencia:

  • Ciencias Farmacéuticas
  • Ciencias de los materiales
  • Química computacional

Sus antecedentes:

  • El polimorfismo en los productos farmacéuticos presenta desafíos en el desarrollo y la fabricación de medicamentos.
  • Los polimorfos inesperados pueden surgir tarde en el desarrollo, aumentando los riesgos.
  • La predicción computacional de la estructura cristalina (CSP) ofrece una solución potencial para explorar paisajes de forma sólida.

Objetivo del estudio:

  • Integrar el estado de la técnica CSP con métodos experimentales para explorar las estructuras cristalinas farmacéuticas.
  • Racionalizar la dificultad para obtener polimorfas específicas y minimizar los riesgos de las formas tardías.
  • Para investigar el paisaje de la forma sólida de isoniazida e iproniazida.

Principales métodos:

  • Se utilizaron técnicas avanzadas de predicción computacional de la estructura cristalina (CSP).
  • Se empleó una amplia gama de métodos experimentales de cristalización, incluidos los experimentos de alta presión.
  • Aplicó cálculos de energía libre para racionalizar las observaciones experimentales.

Principales resultados:

  • CSP predijo con éxito la estructura de la forma III de isoniazida, anteriormente sin resolver durante décadas.
  • El CSP predijo con precisión el riesgo de polimorfismo de la iproniazida.
  • Se obtuvieron y caracterizaron experimentalmente las tres primeras formas cristalinas no solvadas conocidas de iproniazida, todas predichas por CSP.

Conclusiones:

  • El enfoque computacional-experimental sinérgico elimina efectivamente los riesgos de los paisajes de formas sólidas farmacéuticas.
  • La CSP es una herramienta poderosa para predecir y comprender los polimorfos, ayudando al desarrollo de medicamentos.
  • Los experimentos de alta presión tuvieron éxito en la obtención de formas cristalinas evasivas, guiadas por las predicciones de CSP.