This blog post delves into the specific challenges posed by the complexities of interpreting biomedical language with a focus on Named Entity Recognition (NER), setting the stage for a deeper exploration of how Artificial Intelligence (AI) can help.

Manual curation and traditional NLP have limitations holding back our ability to fully leverage available data for drug development decision-making – this post dives into the promise of LLMs to overcome these limitations.

Perspectives from pharma leaders on how we enable AI models to produce high quality outputs to ensure data accessibility and usability.

In this blog post, we dive into the insights shared by pharma experts on the promise AI holds for addressing these challenges.

A recent study published in Journal of Translational Medicine illustrates how the integration of knowledge graph-driven insights into survival prediction and biomarker discovery paves the way for more precise personalised cancer treatments.

3 key areas of data quality in AI are captured by pharma leaders at the recent Festival of Genomics conference: biases in data, incorporation of multimodal datasets and availability of patient-specific data.

Achieving drug development success through the lens of data strategy and Artificial Intelligence (AI) technologies was arguably the hottest topic area at the Festival of Genomics 2025, with key themes emerging across the talks.

2024 has been a year of remarkable technological advancements for the pharmaceutical industry, driven by breakthroughs in Artificial Intelligence (AI). While AI holds immense promise, the challenge for large pharma in 2025 will be executing the right strategies to unlock AI’s full potential and achieve tangible returns on investment.

CSO Ben Sidders speaks with the Journal for Clinical Studies

Biorelate Ltd. CEO and Founder Daniel Jamieson is interviewed alongside other leading pharma thinkers in the PharmaTimes Media Ltd front cover story on reflections and prediction in Pharma

In a fascinating episode of the "Life Science Success" podcast, Dr. Ben Sidders, Chief Science Officer at Biorelate, takes center stage. Host Don Davis, PhD, and MBA, engages in an enlightening conversation with Ben, who shares his journey, insights, and the groundbreaking innovations at Biorelate that promise to reshape the life sciences industry.

Ben Sidders, Chief Scientific Officer at Biorelate explains to Life Sciences Voice why maximizing the potential AI/data-driven model of drug discovery requires the technology’s full integration into R&D

Bio-It World talks to Ben Sidders, Chief Scientific Officer at Biorelate about a framework for transforming R&D outcomes with AI.Find out why a change in the culture is as important as any investment at a data, model, and validation level, for AI to have a tangible impact on R&D success.

Harnessing the potential of AI/data-driven drug discovery requires its optimal integration into R&D says Biorelate’s Dr Ben Sidders.

Dr Sidders brings two decades of deep data science experience, honed across multiple therapeutic areas at Pfizer and AstraZeneca. He will build on Biorelate's strong track record of leveraging advanced data science methods to extract critical knowledge from vast amounts of biomedical literature. These new data-derived insights are enabling drug developers to identify new targets with maximum market potential.

Using Galactic AI™, Biorelate synthesised insights from various biomedical studies into a coherent mechanism that underpins roflumilast's influence on airway inflammation and its prospective clinical benefits for non-CF bronchiectasis patients, by exploring the links between roflumilast and bronchiectasis.

Biorelate Founder and CEO is one of four to be presented with one of the Royal Academy of Engineering’s most prestigious individual awards

Gen AI’s real opportunity in drug development? As a smart, strategic decision aid (Drug Discovery Today)

Staying AI-head of the game!

GenAI’s Real Potential in Biopharma: As a Cross-Function R&D Assistant (BioIT World)

Siloed use of Gen AI will limit its transformation potential

Antonio Fabregat, Knowledge Graph Lead at AstraZeneca, recently presented on the innovations to make data more accessible and insightful for internal biopharma research customers.

Pharmas already have standardised protocols to help them get to the right decision, but it takes them a long time to get there.

Meet Biorelate at The Festival of Genomics and Biodata 2024

Named entity recognition for genes and proteins creates challenges for drug discovery researchers which, luckily, can be overcome by NLP and LLM-curated text mining

To get beyond the universal hype and buzz around ChatGPT, Generative Artificial Intelligence (AI), and Large Language Models (LLMs), ubiquitous across all industries, we brought together biopharma thought leaders to dive into what is hallucination and what is real.

GenAI and LLMs to potentially 'revolutionise' drug discovery - what top pharma thought leaders have to say

Generative AI for Drug Discovery in the era of ChatGPT: The Top 7 Key Considerations For Biopharma