A new open-access platform is consolidating fragmented information about rare diseases into a single searchable hub, helping pharmaceutical and biotech teams make faster, more confident decisions during the earliest and riskiest stages of drug discovery. Explority AI, a company specializing in training artificial intelligence models to advance drug discovery, launched the intelligence hub to bridge the gap between academic research and the pharmaceutical industry.

Why Is Rare Disease Drug Discovery So Fragmented?

Rare diseases affect more than 300 million people worldwide, yet the information needed to identify and evaluate new drug opportunities is scattered across dozens of sources. Population data lives in one registry, current treatments are spread across multiple clinical guidelines, competitive landscapes are scattered across various drug databases, and relevant research is buried in thousands of published papers. This fragmentation forces researchers and business development teams to rebuild the same picture from scratch for every rare disease they investigate, consuming weeks of manual research.

The new hub addresses this inefficiency by consolidating critical information into a single platform. Each of the 5,846 rare disease pages brings together scattered data covering population size, disease burden, gaps in standard care, literature overviews, and live research and drug discovery landscapes for emerging orphan therapies.

What Information Does the Hub Provide?

The directory is organized as a searchable tool where users can explore any of the 5,846 rare diseases to view key metrics and trends. The platform continuously updates as new research is published and new drug designations are granted, eliminating the need for manual tracking. This real-time approach ensures that the landscape stays current without requiring researchers to monitor multiple sources independently.

• Population and Burden Data: Users can access figures on how many people are affected by each disease and the severity of its impact on patients and healthcare systems.
• Standard-of-Care Gaps: The hub identifies unmet medical needs and areas where existing treatments fall short of patient requirements.
• Research and Drug Landscape: A comprehensive view of the volume and pace of new research, plus a table of orphan drug designations associated with each disease.
• Therapy Type Coverage: The hub screens diseases across all therapy types, including small molecules, antibodies, therapeutic proteins, RNA therapies, and gene and cell therapies.

How Does This Accelerate Drug Discovery?

For biotech and pharma teams, consolidating this information means saving weeks of research time and making better-informed decisions at the earliest stage of drug discovery, when the stakes are highest and information is most critical. By making the directory freely available, Explority AI aims to democratize access to disease landscaping information that was previously locked behind paywalls.

"Opening this directory means researchers, R&D and business development teams in pharma no longer have to rebuild that picture from scratch for every rare disease they investigate," said Andrew Obolenskiy, Co-founder and CEO of Explority AI.

Andrew Obolenskiy, Co-founder and CEO of Explority AI

The hub sits alongside Explority AI's core product, which uses large language models (LLMs), a type of artificial intelligence trained on vast amounts of text data to recognize patterns and generate human-like responses, to forecast the probability of success for early-stage therapies across rare diseases. Based on published research, these models rank which drug programs are most likely to succeed in clinical trials years before clinical signals emerge.

Why Are Rare Diseases Becoming a Priority for Pharma?

Orphan therapies, drugs developed to treat rare diseases, now account for a majority of recent FDA approvals. In 2025, orphan therapies represented 54 percent of FDA approvals and generate returns above non-orphan drugs, which has pushed rare disease pipelines up the priority list for pharmaceutical companies, biotech developers, and life-science investors. This shift reflects both the medical need and the financial incentive for companies to invest in treatments for smaller patient populations.

The intelligence hub eliminates a significant bottleneck in the drug discovery process by reducing the risk of decisions based on outdated or incomplete information. Each page is built and continuously updated using a corpus of more than 1 million scientific papers on drug discovery, the same dataset that powers the company's models for forecasting clinical trial success.

How to Use the Hub for Drug Discovery Planning

• Disease Screening: Teams can rapidly screen across all 5,846 rare diseases to identify which conditions have the largest unmet medical needs and least crowded drug discovery landscapes.
• Deal Sourcing and Evaluation: Business development teams can use the hub to evaluate in-licensing opportunities and assess the competitive position of potential acquisitions or partnerships.
• Early-Stage R&D Planning: Research teams can access comprehensive literature overviews and research trends to inform which therapeutic approaches are most promising for specific diseases.
• Risk Assessment: The platform provides context on what therapies have succeeded or failed in clinical trials, helping teams anticipate potential challenges before investing resources.

The free-access model represents a shift in how pharmaceutical research tools are distributed. Most tools built for pharmaceutical research charge for access to basic disease landscaping, which slows down the earliest and most information-heavy stages of drug discovery, exactly when researchers and biotech companies most need clarity on unmet need and emerging opportunities. By removing the financial barrier, Explority AI is aiming to accelerate drug discovery and drug repurposing for rare diseases where new therapies could make the biggest difference to patients with limited treatment options.