Biomarkers increase the success rates of drug development programs, accelerating the path to market and the availability of new therapeutics. Modern translational strategies and precision medicine are rooted in the use of biomarkers – it is estimated that three quarters of the drugs in development in major pharma companies utilize biomarkers in clinical studies. With diverse applications from basic research to post-market safety assessments, drug discovery and clinical teams are leveraging biomarkers to improve target selection, predict drug safety and select trial participants.
Biomarker development is an iterative, multi-step process beginning with discovery, and requiring different levels of validation through analytical validation, clinical qualification and clinical utility. AI can be used to catalyze this process and enable early drug discovery teams to transition discovery projects into clinical programs with confidence.
Identify novel and validated biomarkers
- Easily discover biomarkers - guide your search based on novel biomarkers for more exploratory projects, or focus on biomarkers that are clinically qualified with supporting genetic evidence or demonstrated clinical significance.
Explore a range of applications from preclinical to clinical
- Use Causaly to identify different classes of biomarkers, ranging from biomarkers of disease progression, diagnostic, efficacy and safety biomarkers for early discovery and pre-clinical use cases, through to clinical biomarkers that are more indicative of survival, treatment response and drug resistance.
Prioritize and qualify biomarkers
- Use a range of parameters in Causaly to easily prioritize biomarkers, including the strength of disease linkage, class of biomarker, where it is expressed, availability of preclinical or other experimental data and more. Tailor your process to match your workflow.
- De-risk the selection of biomarkers by considering the availability of assays and measurement methods to detect biomarkers in humans.
Identify novel and validated biomarkers
- Easily discover biomarkers - guide your search based on novel biomarkers for more exploratory projects, or focus on biomarkers that are clinically qualified with supporting genetic evidence or demonstrated clinical significance.
Expedite Biomarker Discovery and Characterization
Evaluate the biological function, expression patterns, disease association, MoA, and relevance to clinical outcomes of biomarkers without the risk of overlooking potential candidates.
Rapidly Validate Biomarkers
Discern true biomarker candidates by effectively filtering out false positives and running comparative analyses in Causaly on experimental data.
Optimize Experimental Design
Determine experimental protocols and biomarker feasibility for use in early clinical trials.
Biomarkers Resources
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Biomarkers of Survival for Duchenne Muscular Dystrophy
DMD is a fatal disease with no cure. Identifying biomarkers linked to DMD patient survival is vital for understanding disease progression, evaluating treatment effectiveness, and enhancing outcomes for those with this rare disease.
Identifying Biomarkers of Crohn’s Disease: IL23
Inflammatory Bowel Disease (IBD) affects millions of people worldwide. In Crohn’s disease, one of the main forms of IBD, biomarkers are pivotal for diagnosis and treatment guidance.
BDNF as a Biomarker for Spinocerebellar Ataxia
Spinocerebellar ataxia is a neurodegenerative disease, affecting 1 to 5 people per 100,000. The identification of biomarkers can provide key insights into the state and progression of a disease, in addition to patient response to treatments. As such, biomarkers can improve the success rates of drug development, accelerating the availability of new therapeutics.
Identifying Blood Biomarkers of Atherosclerosis
Atherosclerosis is one of the leading causes of death worldwide. Biomarkers play a crucial role in comprehending atherosclerosis, providing measurable indicators of disease presence, progression, and treatment response.
Hormone Biomarkers for Alzheimer’s Disease: Corticosterone vs. Cortisol
Alzheimer’s disease (AD) is the most prevalent form of dementia. An estimated 6.5 million Americans aged 65 and older are living with Alzheimer’s dementia, a figure which is projected to soar to around 14 million by 2060. Current treatments only offer temporary symptomatic relief, highlighting the importance of AD research.
Exploring Biomarkers for Sickle Cell Disease
Since the 1950s, more than 500 biomarkers for SCD have been reported in the literature, according to Causaly data. Comparing this to more common blood diseases such as leukemia, which has over 10x more biomarkers reported, highlights the significant unmet need in the rare disease research.
Insights from our talk at Biomarkers 2023: The use of human-centric AI in biomarker identification in Oncology and Immunology
Biomarkers 2023 was held in Manchester, UK on the 27th and 28th of February. The event brought together a diverse group of experts, across pharma, biotech, and academic institutions.