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Translational Scientist

As a translational scientist, you play a pivotal role  in bridging the gap between preclinical findings and clinical applications. Our platform is designed to help you decode disease mechanisms, reconcile disparate research findings, predict potential clinical outcomes, and design effective translational strategies with ease and precision. With Causaly, uncover intricate disease-pathway correlations, identify promising therapeutic targets, and generate actionable insights faster than ever before. Join us in accelerating therapy development and innovating therapeutic translation, driving the future of translational medicine and contributing to breakthroughs in life sciences.

Translational Scientist with vials

Target & Disease Biology

Use AI to uncover hidden mechanistic connections in the literature.

Comprehensive Analysis

Investigate the vast biomedical literature, enriching your understanding of target and disease biology.

Novel Insight Discovery

Uncover hidden relationships and connections, revealing new insights into disease mechanisms and potential therapeutic targets.

Efficiency Enhancement

Navigate through immense biomedical data swiftly, accelerating your study of disease and target biology.

“Using the Advanced Search tool, I can get really detailed and precise insights in terms of relationships between molecules and disease”
Translational Research Scientist
“What motivates me to use Causaly is the complex network analysis because it allows me to identify connections that are not obvious. The strength of evidence are of immense value to me because you can assess all the evidence in a very quick and straightforward way”
Lab Head
Global Imaging Mass Spectrometry Biomarker Discovery Platform
“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
“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”
Biomarker Identification Specialist
“Using the Advanced Search tool, I can get really detailed and precise insights in terms of relationships between molecules and disease”
Translational Research Scientist
“What motivates me to use Causaly is the complex network analysis because it allows me to identify connections that are not obvious. The strength of evidence are of immense value to me because you can assess all the evidence in a very quick and straightforward way”
Lab Head
Global Imaging Mass Spectrometry Biomarker Discovery Platform
“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
“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”
Biomarker Identification Specialist

Translational Scientist Resources

Unraveling Mechanisms of Disease Pathogenesis with AI Featured Image
Anna Tzani • March 6, 2024

Unraveling Mechanisms of Disease Pathogenesis with AI

AI-supported investigations into disease mechanisms offer a transformative approach to understand complex pathologies. By leveraging AI to unlock disease understanding, researchers can identify novel biomarkers and therapeutic targets with unprecedented precision. This not only accelerates the journey from lab to market but also enhances the efficacy and safety of new treatments.

Comparison of Safety Biomarkers for Chemotherapeutics Featured Image
Anna Tzani • February 9, 2024

Comparison of Safety Biomarkers for Chemotherapeutics

The identification and utilization of safety biomarkers plays a key role in mitigating toxicity risks and reducing costs in drug development, thereby accelerating the delivery of safe and effective drugs to patients. AI can streamline the identification of relevant biomarkers from the ever-growing biomedical literature, offering insights into drug resistance and toxicity.

Challenging the Status Quo: A Biomarker Use Case Featured Image
Anna Tzani • January 24, 2024

Challenging the Status Quo: A Biomarker Use Case

Traditional keyword searching is highly inefficient, subject to bias and is not always comprehensive, providing limited potential for knowledge discovery and hypothesis generation. This selective approach introduces a bias towards familiar areas of expertise, which can lead to missed opportunities for novel insights and innovations. This is where AI comes in.

Uncovering the Mechanism of Action of Evolocumab against PAD Featured Image
Anna Tzani • January 12, 2024

Uncovering the Mechanism of Action of Evolocumab against PAD

Deciphering a drug’s MoA is crucial for making informed decisions in drug development, paving the way for the development of more targeted and effective therapeutic solutions. AI can revolutionize this process by facilitating knowledge discovery without bias, unveiling hidden drug-disease interactions.

Target-Based Drug Discovery Begins with Understanding Disease Pathophysiology Featured Image
Anna Tzani • January 5, 2024

Target-Based Drug Discovery Begins with Understanding Disease Pathophysiology

Target-based drug discovery begins with understanding the physiological basis of the disease, and the subsequent abnormal or deviant pathways and targets responsible for the disease phenotype.¹ A foundational understanding of disease pathophysiology therefore serves as a roadmap for drug development success.

Biomarkers of Treatment Response in Liver Cancer Featured Image
Anna Tzani • December 7, 2023

Biomarkers of Treatment Response in Liver Cancer

Biomarkers serve as objective measures of treatment response to guide patients towards the most appropriate therapies. Yet, in the era of big data, pinpointing promising biomarkers remains a challenging endeavor. AI is revolutionizing translational medicine by improving the efficiency and accuracy of biomarker identification. Here, we used Causaly to identify and prioritize biomarkers of sorafenib […]

Expedite Biomarker Discovery with Human-Centric AI Featured Image
Anna Tzani • December 4, 2023

Expedite Biomarker Discovery with Human-Centric AI

Biomarkers are pivotal throughout drug development, from discovery to market, playing key roles in unravelling drug mechanisms, providing prognostic insights and assessing treatment efficacy. Despite the clinical promise, biomarker development is challenging. There are substantial obstacles, from disease heterogeneity and rigorous validation requirements to the inability to extract meaningful biomarker insights from extensive biological data.

Biomarker Identification and Prioritization: GERD Featured Image
Anna Tzani • November 24, 2023

Biomarker Identification and Prioritization: GERD

Biomarker-based strategies have shown to improve drug program success. However, biomarker discovery is marked by the intricate challenge of extracting relevant molecular signatures from extensive biological data. In this use case, we demonstrate how Causaly can be used to understand the biomarker landscape in GERD, a common digestive disorder characterized by chronic acid reflux.

Biomarkers of Imatinib Resistance in Chronic Myeloid Leukemia Featured Image
Anna Tzani • November 22, 2023

Biomarkers of Imatinib Resistance in Chronic Myeloid Leukemia

With oncology pivotal trials averaging $32 million and a 95% drug failure rate, there is a growing interest in leveraging biomarkers for treatment optimization. Notably, drug resistance biomarkers are key in identifying treatment sensitivity, adjusting treatment protocols, and improving survival rates.

Identifying Prognostic Biomarkers of Pancreatic Cancer Featured Image
Anna Tzani • November 9, 2023

Identifying Prognostic Biomarkers of Pancreatic Cancer

Pancreatic cancer is one of the most aggressive and fatal cancers worldwide. Treatment efficacy is a major concern, and there is a pressing need for reliable prognostic biomarkers to improve patient outcomes. Here, we used Causaly to uncover potential biomarkers for this disease.

Identifying Urine Biomarkers of Chronic Kidney Disease Featured Image
Anna Tzani • October 26, 2023

Identifying Urine Biomarkers of Chronic Kidney Disease

Monitoring disease progression is crucial for timely interventions in CKD. Urine biomarkers, such as RBP4, offer potential in CKD detection and disease tracking. Using Causaly, Retinol-Binding Protein 4 (RBP4) was identified as a potential urine biomarker of CKD progression with untapped potential.

Disease Progression Biomarkers: Huntington’s Disease Featured Image
Anna Tzani • October 19, 2023

Disease Progression Biomarkers: Huntington’s Disease

Although challenging, the development of biomarkers for neurodegenerative diseases is a critical endeavor. In this use case, we explore potential blood biomarkers for the progression of Huntington’s Disease (HD), a rare neurological condition.

Biomarkers of Survival for Duchenne Muscular Dystrophy Featured Image
Anna Tzani • September 11, 2023

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 Featured Image
Anna Tzani • August 23, 2023

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 Featured Image
Anna Tzani • August 21, 2023

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 Featured Image
Anna Tzani • August 15, 2023

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.

Anna Tzani • August 7, 2023

Biomarkers of Treatment Response in Sarcoma

In the evolving landscape of modern medicine, biomarkers are at the forefront of clinical research. Biomarkers can serve as objective measures of treatment response, guiding patients towards the most suitable therapies and reducing the risk of unnecessary and potentially harmful treatments.

Hormone Biomarkers for Alzheimer’s Disease: Corticosterone vs. Cortisol Featured Image
Anna Tzani • 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 Biomarkers for Sickle Cell Disease Featured Image
Anna Tzani • June 19, 2023

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 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.