Reinventing Drug Candidate Selection
Late-stage failures are expensive, and many could have been prevented if the right information and data had been available earlier in the drug development process. This is particularly relevant to drug safety and regulatory approvals, where evidence-based information, such as that found in FDA and EMA drug approval documents, offers insights that can help reduce time spent in development and navigating regulatory approval cycles – which can mitigate the likelihood of late-stage failures.
Elsevier R&D Solutions improve risk and benefit analyses by providing supportive and comparative drug safety precedent data. This data enables pharma professionals to make better-informed scientific, business and regulatory decisions that ensure development processes happen on time and within budget, including informing preclinical study designs with precedent information on drugs in the same or similar classes.
Elsevier R&D Solutions for Pharma & Life Sciences
Embase increases the discovery of biomedical evidence to support critical life sciences functions, delivering relevant, up-to-date biomedical information to the global research community.
PharmaPendium provides the comparative and up-to-date information needed to verify pharmacokinetic and experimental data, anticipate species-specific issues in translating in vitro and in vivo studies, and predict potential drug–drug interactions, and design clinical trial studies to comply with regulatory requirements.
Elsevier R&D Solutions Professional Services team helps drive pharmaceutical research in innovative directions by resolving challenges with data quality and integration, resulting in data that is easier to compare, analyze, interpret and share.
Elsevier’s customized Text Mining service provides meaningful answers to complex questions through the retrieval of highly specified information from unstructured content.
Real Stories. Real Science. Real Time.
Visit the Hive to explore how biotech and pharma start-ups are using Elsevier R&D solutions to solve for early-stage drug discovery and development. Watch videos, read real-world case studies and learn how early innovation starts with rapid results and early access to research that is crucial to reducing the likelihood of costly late stage failures and mitigating risk.
Reducing the Likelihood of Late-Stage Failures
Investments in pre-clinical research can improve your chances for downstream success.
Using In Silico Models to Predict Clinical Outcomes
What aspects of drug candidate selection can be improved with the application of in silico methods? This article shows the power in numbers.
Reaching toward Integrated Data Approaches for Improved Drug Safety
An integrated approach to big data and in silico profiling has incredible potential for predicting drug safety. What is the current state of this field of informatics?
The Perfect Gatekeeper
A strong, safe and effective companion diagnostic is at the core of precision medicine. The development workflows of a targeted drug and its coupled diagnostic test are highly interconnected, leading to potential benefits, but also demanding high-quality information at every step.
Need expertise for data retrieval and mining?
Elsevier helped a pharmaceutical company find new indications for a drug through high-quality text-mining solutions.
Read the case study (PDF, 682kb)