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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.

Discover Biomarkers with Ease introduction image

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.
Identify novel and validated biomarkers

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.
Explore a range of applications from preclinical to clinical

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.
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  • De-risk the selection of biomarkers by considering the availability of assays and measurement methods to detect biomarkers in humans.
Prioritize and qualify biomarkers

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.
Identify novel and validated biomarkers

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.

"Causaly allows you to gain a quick overview of the therapeutic area very quickly with the dendrogram view. It would otherwise take a tremendous amount of time to do this on my own reading articles on PubMed."
Translational Research Scientist
Top 50 Pharma
"One of the most valuable things about Causaly is that it doesn't cost you time in the lab. You can find something on the platform and look at the experiments performed; what are the methods used, can they be reproduced, do you agree with the results. This helps with understanding what validation experiments to conduct."
Data Science Specialist
Top 50 Pharma
"What motivates me to use Causaly is the complex network analysis because it allows me to identify connections that are not obvious. The biggest impact on my specific role is when I work on the untargeted characterization of biomarker relationships."
Lab Head Global Imaging Mass Spectrometry Biomarker Discovery Platform
Top 50 Pharma
"The strength of evidence in Causaly are of immense value to me because you can assess all the evidence in a very quick and straightforward way."
Lab Head Biomarker Discovery Platform
Top 50 Pharma
"I use Causaly to identify suitable biomarkers and get an idea of feasibility for use in first-in-human dose trials and Phase 1 trials. Manual research in PubMed and Google takes significantly longer and the risk of missing out on something important is much greater."
Biomarker Identification Specialist
Top 50 Pharma
"Causaly allows you to gain a quick overview of the therapeutic area very quickly with the dendrogram view. It would otherwise take a tremendous amount of time to do this on my own reading articles on PubMed."
Translational Research Scientist
Top 50 Pharma
"One of the most valuable things about Causaly is that it doesn't cost you time in the lab. You can find something on the platform and look at the experiments performed; what are the methods used, can they be reproduced, do you agree with the results. This helps with understanding what validation experiments to conduct."
Data Science Specialist
Top 50 Pharma
"What motivates me to use Causaly is the complex network analysis because it allows me to identify connections that are not obvious. The biggest impact on my specific role is when I work on the untargeted characterization of biomarker relationships."
Lab Head Global Imaging Mass Spectrometry Biomarker Discovery Platform
Top 50 Pharma
"The strength of evidence in Causaly are of immense value to me because you can assess all the evidence in a very quick and straightforward way."
Lab Head Biomarker Discovery Platform
Top 50 Pharma

Biomarkers Resources

Hormone Biomarkers for Alzheimer’s Disease: Corticosterone vs. Cortisol Featured Image
Andrew Taylor • July 6, 2023

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 Diagnostic Biomarkers for Sickle Cell Disease Featured Image
Andrew Taylor • June 19, 2023

Exploring Diagnostic 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 Featured Image
Maria Tella • March 3, 2023

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.