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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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Developing PreDICT - a fully integrated data platform for preclinical in vivo data: learning from experience.

Rhys D O Jones¹, Marie Cooke², James Hinchliffe³

¹IMED Oncology, AstraZeneca Oncology, Cambridge, UK.

Drug Discovery Today

|August 13, 2017

Summary

This summary is machine-generated.

Managing complex in vivo data for drug development is challenging. This project successfully integrated pharmacokinetic, biomarker, and efficacy data across various models, improving data analysis for novel therapeutics.

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Area of Science:

Pharmacology and Toxicology
Biomedical Data Science

Background:

In vivo models are essential for understanding human diseases and developing new therapeutics.
Current in vivo studies generate complex datasets, including pharmacokinetics, biomarkers, and efficacy, posing data management challenges.
Integrating diverse data types from multiple drug investigations and combinations is an industry-wide hurdle.

Purpose of the Study:

To develop and present a unified solution for integrating complex in vivo data.
To address the ongoing challenge of managing diverse datasets in preclinical research.
To create a therapy-area-independent data integration system.

Main Methods:

Described a project focused on data integration.
Developed a working solution for combining pharmacokinetic, biomarker, and efficacy data.
Ensured the solution is applicable across different therapeutic areas.

Main Results:

Successfully delivered a functional system for in vivo data integration.
The solution integrates pharmacokinetic, biomarker, and efficacy data effectively.
The system is independent of specific therapy areas, offering broad applicability.

Conclusions:

A successful, therapy-area-independent solution for integrating complex in vivo data has been developed.
This approach can streamline data analysis and support the development of novel therapeutics.
Effective management of integrated in vivo data is achievable and crucial for drug discovery.