Resources

If you need more information feel free to contact our Help Center

The Agent Harness That Makes Scientific AI Work

In biopharma R&D, the model alone does not determine whether a system is useful, trusted, or deployable inside a scientific workflow. The decisive layer is the harness around the model

Yiannis Kiachopoulos

March 10, 2026

Blog

Discover the latest reports, data sheets, articles, infographics, and videos on biomedical R&D and AI.

The Agent Harness That Makes Scientific AI Work

Yiannis Kiachopoulos

March 10, 2026

In biopharma R&D, the model alone does not determine whether a system is useful, trusted, or deployable inside a scientific workflow. The decisive layer is the harness around the model

The FDA’s New Guiding Principles for AI in Drug Development

Team Causaly

January 29, 2026

Causaly has been building toward this standard long before it was formalized, by designing Agentic Research that reasons within a scientific context, generates evidence-centric outputs, and supports accountability by design.

Agentification in Biopharma R&D: How To Turn Workflows Into Executable Systems

Yiannis Kiachopoulos

January 27, 2026

Agentification in biopharma R&D does not start with agents. It starts with workflow, SOPs, and protocols. Places that already have structure, expectations, and consequences.

Context Graphs: A Prerequisite for Agentic AI in Enterprises

Yiannis Kiachopoulos

January 21, 2026

If you want reliability, reproducibility, and sustained adoption, context must be treated as a first-class product layer rather than an afterthought.

From Copilots to Agentic Workflows: How AI in R&D Changes in 2026

Yiannis Kiachopoulos

January 6, 2026

In 2026, the wedge will be who can turn scientific work into executable units—use cases and workflows that are decomposed into precise steps, run with predictable structure, and produce reviewable artifacts with provenance.

How Termination Conditions Strengthen Agentic Systems in R&D

Yiannis Kiachopoulos

December 16, 2025

In practice, termination is a function of coverage saturation, diminishing returns, decision risk, and the artifacts required for the task.

Unraveling Mechanisms of Disease Pathogenesis with AI

Anna Tzani

March 6, 2024

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.

Leveraging AI for Scientific Knowledge Extraction

Anna Tzani

February 13, 2024

AI is transforming the analysis of extensive biomedical data, allowing pharma companies to expedite R&D processes, and cut costs. By reaching conclusions quicker, the inclusion of AI in drug development pipelines can inform decision-making, enabling the prioritization of more promising research avenues.

Exploring the Disease Pathophysiology of Rheumatoid Arthritis

Anna Tzani

February 6, 2024

Understanding the pathophysiology of a disease is pivotal in comprehending its cause and progression and facilitating the identification of novel targets for therapeutic intervention. Data-driven strategies are essential in navigating this complexity, facilitating a deeper understanding of disease pathophysiology, which can be leveraged to develop more effective treatments.

Search by Target Class: Enzyme Targets for Celiac Disease

Anna Tzani

January 26, 2024

The strategic prioritization of drug targets by target class can be used to streamline discovery, enabling efficient resource allocation and time-savings in early drug development, as well as a competitive edge given the variable success rates of different target classes. Prioritization of specific target classes may therefore enable investment optimization in preclinical research.

Navigating the Biomedical Literature: Insights vs. Papers

Anna Tzani

January 19, 2024

With 2 publications added to PubMed every minute, identifying therapeutic targets with traditional keyword searching is time-consuming, causes reading fatigue and is subject to bias. By machine-reading the literature, Causaly manages this data overload, extracting scientific insights rather than papers, to enable the exploration of more novel avenues.

Uncovering the Mechanism of Action of Evolocumab against PAD

Anna Tzani

January 12, 2024

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.

ProQR Uses Causaly to Support Target Identification For Axiomer™ Platform

Yiannis Kiachopoulos

January 28, 2025

ProQR faced challenges with bandwidth, aggressive targets, and the overwhelming growth of biomedical literature. Causaly's AI platform accelerated ProQR’s R&D by enabling faster review of publications and allowing their team to make more informed decisions. Read the case study below to learn how ProQR met their 2024 target ID goal by Q3 and achieved 5x productivity compared to using PubMed.

Enhance Your Search Sensitivity with AI: Off-Target Effects of BRAF

Anna Tzani

February 29, 2024

In contrast to conventional keyword searching techniques, Causaly’s AI can sift through and remove irrelevant data from biomedical searches, offering a more thorough and accurate understanding of entire research landscapes. This not only streamlines knowledge acquisition but ensures accuracy and precision in navigating the biomedical literature.

Leveraging AI for Scientific Knowledge Extraction

Anna Tzani

February 13, 2024

AI is transforming the analysis of extensive biomedical data, allowing pharma companies to expedite R&D processes, and cut costs. By reaching conclusions quicker, the inclusion of AI in drug development pipelines can inform decision-making, enabling the prioritization of more promising research avenues.

Search by Target Class: Enzyme Targets for Celiac Disease

Anna Tzani

January 26, 2024

The strategic prioritization of drug targets by target class can be used to streamline discovery, enabling efficient resource allocation and time-savings in early drug development, as well as a competitive edge given the variable success rates of different target classes. Prioritization of specific target classes may therefore enable investment optimization in preclinical research.

Navigating the Biomedical Literature: Insights vs. Papers

Anna Tzani

January 19, 2024

With 2 publications added to PubMed every minute, identifying therapeutic targets with traditional keyword searching is time-consuming, causes reading fatigue and is subject to bias. By machine-reading the literature, Causaly manages this data overload, extracting scientific insights rather than papers, to enable the exploration of more novel avenues.

Eliminating Bias with Human-Centric AI

Anna Tzani

January 9, 2024

Traditional keyword searching can miss crucial information, skewing representations of research landscapes before reading even begins. Instead, Causaly’s human-centric AI can extract all targets for a given disease without bias, uncovering scientific insights, rather than just papers.

Aiding Drug Repurposing Investigations with AI

Anna Tzani

February 23, 2024

Drug repurposing offers a cost-effective and efficient pathway to discovery new therapeutic uses for existing treatments. AI can advance this process by rapidly analyzing large-scale biomedical data and scientific texts to identify drug-disease relationships, opening up avenues for treatments in unexplored indications.

Comparison of Safety Biomarkers for Chemotherapeutics

Anna Tzani

February 9, 2024

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.

AI-Powered Drug Discovery: Identifying Safety Red Flags

Anna Tzani

January 30, 2024

Unmanageable toxicity accounts for 30% of clinical drug development failures and can cause severe side effects and potential harm to patients. Download our report to see how AI-powered drug discovery can help mitigate late-stage clinical failures and market withdrawals.

Comparison of Safety Biomarkers for Chemotherapeutics

Anna Tzani

February 9, 2024

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

Anna Tzani

January 24, 2024

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.

Biomarkers of Treatment Response in Liver Cancer

Anna Tzani

December 7, 2023

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.

Expedite Biomarker Discovery with Human-Centric AI

Anna Tzani

December 4, 2023

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.

News

The latest news and updates from Causaly.

news

How Agentic AI Learns to Think Like a Scientist

Team Causaly

January 14, 2026

What happens when AI stops guessing and starts reasoning? Agentic AI is bringing scientific logic into the heart of drug discovery.

news

Causaly Launches Agentic AI Platform to Transform Life Sciences R&D

Team Causaly

October 9, 2025

Causaly has unveiled Causaly Agentic Research, a breakthrough agentic AI platform purpose-built for life sciences research and development.

news

Causaly Introduces First Agentic AI Platform Built for Life Sciences Research and Development

Team Causaly

September 16, 2025

Specialized AI agents automate research workflows and accelerate drug discovery and development with transparent, evidence-backed insights

news

Causaly Launches AI-powered Competitive Intelligence Application for Research Scientists

June 24, 2025

New Pipeline Graph unifies competitive insights with preclinical research on a single AI platform to accelerate drug target identification and increase commercial success

news

Causaly Announces Agentic AI for Scientific Discovery

Team Causaly

March 31, 2025

New AI agents in Causaly Discover empower scientists to answer complex biomedical questions faster and more accurately across a broader range of sources

news

How generative AI is transforming early Drug Discovery: Insights from Novartis’ Jeremy Jenkins at Hariri Institute, Boston

Team Causaly

November 7, 2024

Keynote Spotlight: Jeremy Jenkins on Generative AI in Early Drug Discovery

Events and Webinars

Our events and webinars on demand and dig deeper into the next era of scientific research.

Webinar

Agentic AI and the New Pace of Drug Discovery

March 12, 2026

Join Manas AI co-Founder, CEO and distinguished author Dr. Siddhartha Mukherjee, alongside Causaly CEO and Co-Founder Yiannis Kiachopoulos, for a gripping discussion exploring how AI is can carry out scientific reasoning in R&D.

Watch now

Webinar

Autonomous AI Agents for Life Sciences R&D

No items found.

October 15, 2025

In this exclusive webinar, we showcased Agentic Research by Causaly. Our groundbreaking technology that redefines R&D processes with the implementation of autonomous AI research agents.

Watch now

Webinar

The Business Case for AI with Novartis and Gartner

No items found.

August 14, 2025

In this webinar, experts from Gartner and Novartis join the Causaly team to share their insights into the latest AI technologies transforming life sciences, and how to put those AI tools to work in real world pharma use cases.

Watch now

Webinar

Bring Competitive Intelligence to your Scientific Research

No items found.

June 24, 2025

Join us for an exclusive webinar where we’ll showcase Causaly's Pipeline Graph, our latest AI-powered application that brings competitive insights upstream to compare programs, de-risk early decisions, and optimize R&D investment.

Watch now

Webinar

Move from Simple Search to Transformative Insights with AI

No items found.

March 25, 2025

Join us for an exclusive webinar where we’ll showcase Causaly Discover, our latest AI-powered research application that transforms the way scientists carry out their research.

Watch now