Efficient drug discovery hinges on researchers’ ability to access essential data at critical decision points to make informed choices. Drug developers must be able to answer fundamental questions like:
- Should we pursue this drug class further?
- What are the effects of recent molecular changes on drug safety and efficacy?
- Which investigational compounds should we prioritize for development?
Research and development team leaders often spend too much time managing data across applications. These tedious activities distract from their core tasks like analyzing molecular structure-activity relationships and planning their next research steps. Moreover, transferring data between different sources and applications risks losing context and degrading data quality.
Researchers need a robust solution to unify data sources into a coherent and consistent format to prevent these issues. Ideally, researchers should use a drug discovery tool that is versatile and capable of processing small-molecule drugs and biological agents like oligonucleotides, peptides, and antibodies.
How Drug Discovery Tools Use Data to Support Pharmaceutical Industry Decision-Making
In drug development, maximizing efficacy while minimizing side effects is paramount. Researchers depend on diverse data, revealing extensive details about an active ingredient’s chemical, structural, and biological properties. This data encompasses biological test evaluations, such as how active ingredient molecules interact with certain enzymes, and results from computer-aided modeling.
Moreover, pharmaceutical teams often incorporate data from external research partners, including findings in scientific publications and public research databases. Researchers must integrate these external results with their in-house data to form a comprehensive dataset for further analysis.
A company’s data infrastructure determines research teams’ efficiency in using data from various sources for analyzing and understanding drug safety, efficacy, and physiochemical parameter relationships.
Data Infrastructure Should Allow Easy Data Access, Analysis, and Collaboration
Certara has an innovative solution to these challenges: D360 drug development software. This specialized scientific informatics platform empowers pharmaceutical R&D professionals to leverage data from diverse sources, accelerating the discovery process. That’s why over 6,000 research scientists worldwide from the top 10 pharmaceutical companies to biotech startups use the D360 drug discovery tool to improve data utilization and optimize their design-make-test-analyze cycles.
The D360 scientific informatics platform, specialized for pharmaceutical research and development, consolidates data from diverse sources into a unified view. It can aggregate data related to active ingredient candidates from various sources into a single dataset for analysis.
D360 allows researchers to query the databases for the needed data and present it in an insightful and easily configurable way. Moreover, the system employs everyday research terms, eliminating the need for programming or specialized database querying knowledge. The system prepares the data for further analysis with integrated software functions, such as medicinal chemical analysis, diverse graphical evaluations, multi-parameter scoring, molecule annotation, formula calculation, and data exchange with external partners. Scientists can save their searches’ data formatting and tailored analysis viewers so that future searches provide them with an up-to-date, analysis-ready dataset. Project team members can easily share every search and dataset.
Image 1: Data visualization tools in D360.
Figure 2: Transformation analysis showing the influence of changes in molecular structure on biological activity and molecular properties.
The Outlook for Scientific Informatics is Bright!
Certara’s data science experts are enhancing D360 to interpret and utilize complex data formats previously deemed unsuitable for analysis, thus unlocking new research possibilities. D360 leverages our artificial intelligence and deep learning platform to extend its analysis capabilities to unstructured data, identifying molecules and active ingredient names across varied documents such as internal reports or scientific publications, and linking them to corresponding substances.
Watch this webinar to learn more about how D360 is helping the pharmaceutical industry speed time to insight.