Resources

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

From the Lab’s Biggest AI Skeptic to Its Advocate

Jessica Armand spent five years studying drug resistance in breast cancer and told everyone in her lab not to trust AI. Now she's an AI advocate and onboards skeptical scientists onto the Causaly platform.

Jessica Armand

August 26, 2026

Blog

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

From the Lab’s Biggest AI Skeptic to Its Advocate

Jessica Armand

August 26, 2026

Jessica Armand spent five years studying drug resistance in breast cancer and told everyone in her lab not to trust AI. Now she's an AI advocate and onboards skeptical scientists onto the Causaly platform.

How Causaly's Scientific Workflows turn weeks of competitive analysis into cited, board-ready assessments.

Anton Tcholakov

August 20, 2026

SOPs provide rigor, but manual execution limits speed and scale. Causaly’s Scientific Workflows use coordinated AI agents to deliver the same rigor with greater speed, breadth, and scalability.

Why a Correct Decision is More Important Than Saving Time in Drug Discovery

Stravroula Ntoufa

August 17, 2026

Stavroula Ntoufa spent 14 years in academia before joining Causaly. She argues that the most valuable thing in pharma R&D is the judgment a scientist applies at every decision gate. But this expert decision-making isn’t written down anywhere. AI agents are changing that.

Why Data and LLMs Alone Cannot Create Scientific Outcomes

Yiannis Kiachopoulos

August 11, 2026

Enterprises have valuable scientific data and increasingly capable models. A scientific harness and enterprise transformation turn that capability into work R&D can trust and use.

How Causaly Solutions Support Portfolio Decisions

Kaz Lewis

August 10, 2026

Evidence-grade workflows that allow your team to spend more time on judgement calls, not evidence gathering.

An AI Scientist Is Proven by the Science It Produces

Yiannis Kiachopoulos

August 4, 2026

An analysis of patient responders and nonresponders can contain the right data, methods, evidence, and citations and still reach the wrong conclusion. Building a trustworthy AI scientist requires calibrating the complete system against one key scientific outcome at a time.

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

Causaly and Syneos Health Partner to Raise the Scientific Intensity of Clinical Research

Team Causaly

August 18, 2026

Collaboration embeds evidence-grounded agentic AI into scientific workflows across Syneos Health,accelerating research while strengthening scientific rigor, consistency, and sponsor value

news

Causaly and Sage Bring Full-Text Scientific Literature into AI-Powered Drug Discovery Research

Team Causaly

July 29, 2026

Partnership allows Causaly AI agents to access and read full-text of Sage journal articles and deliver the most relevant insights directly within the Causaly platform, helping mutual customers unlock deeper evidence from their existing institutional licenses

news

Microsoft and Causaly Integration Accelerates Biopharma R&D Through AI-Driven Scientific Reasoning

June 29, 2026

The technical significance of this integration lies in its ability to move beyond simple ‘horizontal’ AI tools.

news

Causaly, Microsoft link computation and scientific reasoning

June 29, 2026

The workflow aims to help biopharma teams assess targets, biomarkers, safety and mechanism questions with cited evidence.

news

Causaly and Microsoft target one of drug discovery’s most expensive decisions: which target to pursue

June 29, 2026

What compresses is the knowledge work, the analytical layer that sits on a program’s critical path: building a baseline of what’s known, drafting protocols, reviewing safety, selecting candidates.

news

Causaly and Microsoft Collaborate to Connect Scientific Computation to Scientific Decision-Making for Life Sciences R&D

June 2, 2026

Helping R&D teams move from raw internal data to cited, defensible scientific decisions in a single governed workflow —setting a new standard for speed, rigor, and provenance in drug discovery and development

Events and Webinars

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

Webinar

Causaly Dissected: Clinical Development - Building the Case Before the Trial

No items found.

August 12, 2026

In this episode of Causaly Dissected our scientists take one of the highest stakes workflows in Clinical Development, building the evidence case before a single patient is enrolled, and walk through it live in Causaly.

Watch now

Webinar

Evidence at the Speed of Science: How Leading Pharma Is Putting AI to Work in R&D

July 30, 2026

Takeda's Head of Computational and Systems Biology on how his team applies AI to indication expansion, mechanism of action work, and everyday R&D decisions.

Watch now

Webinar

Causaly Dissected: Reducing Scientific Uncertainty in Translational Medicine

July 8, 2026

In this episode of Causaly Dissected, our scientists take one of the highest-stakes TxMed workflows, target validation and translational evidence synthesis, and walk through it live in Causaly.

Watch now

Webinar

Automate Your Research Workflows - From Question to Confident Decision

No items found.

June 17, 2026

Join us for an exclusive look at Scientific Workflows by Causaly. The governed agentic automation solution moving life sciences R&D from scientific intelligence to scientific execution.

Watch now

Webinar

Causaly Dissected: Accelerating Medical Affairs with Agentic AI Research

June 10, 2026

About the series: Causaly Dissected is our monthly live demo series. Each 30-minute episode takes one life sciences use case and pulls it apart in real time. The workflow mirrors the use cases staring with a scientific question, and running through all the critical next steps including the agentic research run, the cited evidence, and the deliverable a working scientist would actually hand to a colleague.

Watch now

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