The client is conducting a first-in-human trial of a treatment for osteoarthritis and needs to assess its performance against competing therapies and determine the appropriate sample size for the pivotal trial. There are too many articles to review manually and identify the information relevant to this specific question.
We extracted structured information from public-domain literature using our proprietary Bio|Reflect® tool, with iterative refinement of the outcomes and rigorous data quality checks. In total, we extracted 150 relevant data points from more than 5,000 that were collected from 900 publications, achieving 90% precision.
Our work enabled a more accurate, cost-effective trial design through data-driven power calculations, helping accelerate the path to market.
The approach gave the client a data-driven view of the competitive landscape and clinical evidence. By enabling a more accurate trial design and sample size calculation, it helped reduce unnecessary costs and timelines while increasing confidence in the path to market.
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For over a century, the life sciences industry has relied on animal models as the standard for predicting drug safety and effect. But today, the industry faces a harsh reality: over 90% of new drugs that appear safe and effective in animal tests ultimately fail in human clinical trials (see for example Ineichen et al. 2024 [1] and Marshall et al. 2023[2])
Oncology drug development often begins in patients, allowing early safety and efficacy insights. Yet many cancer drugs still fail in the clinic. We validate the target but ignore its context within the tumor microenvironment. This article explores why spatial biology may improve clinical success.
BioLizard has been named “Bioinformatics Innovation of the Year” in the 2025 BioTech Breakthrough Awards. The honor spotlights Bio|Verse® Navigator, a visual analytics workspace that unifies complex R&D data so scientists can decide faster, with confidence.
