Achievements / Value-add
- Sped up 10x the discovery of new therapeutic insights – gained access to unified knowledge from proprietary data and over 30 public datasets and literature sources
- Expert-curated information access – utilizing Ontotext’s specialized knowledge base to swiftly identify the most relevant information sources
- Significantly accelerated lab validation process – from a few days per target to a couple of minutes
- Tailored workflows – easily adapted the software for various therapeutic areas, drug repurposing, target and biomarker discovery, or compound prioritization
The Goal
A team from a global collaboration center in Massachusetts wanted to speed up their cancer research and bring new, safe, and efficient drugs to patients faster. Their main goal was to find new therapeutic approaches to cancer and they started by contextualizing their internal data. For this particular project, the team needed to prioritize over 5,000 genes for wet lab validation and evaluate their therapeutic relevance efficiently.
The Challenge
The most significant challenge for the team was the extensive data they had generated, yielding over 5,000 potential targets that needed screening. This vast amount of data required considerable manual work and dedicated internal resources to expedite the process. Each gene had to be screened for basic biological data such as expression, pathway participation, and protein crystal structure.
On top of that, it had to be evaluated for novelty (how well studied was it in the recent literature in the context of cancer), druggability (were there any compounds that already targeted the gene and if so, at what stage of clinical research were they), variants, and disease relevance (causality, association, preventive potential). Before using Ontotext’s solution, the team had to sift through all of this data manually and work through confusing and irrelevant information. It was also slow and tedious to evaluate all the data and make decisions
To achieve optimal results, they had to rely on existing knowledge from trusted sources. Often, the researchers would try to prioritize targets solely based on the limited amount of internal data, which didn’t always work out and the decision-making process lacked evidence about the strength of the gene-disease relationship.The team, comprising experts from structural biology, discovery science, medicinal chemistry, translational pharmacology, and computational biology, also faced the challenge of integrating diverse backgrounds to foster collaboration and meet each discipline’s needs.
The Solution: AI-augmented target mining with Ontotext’s Target Discovery
Ontotext’s Target Discovery offered the researchers a wealth of information directly relevant to cancer research. This included data on diseases, potential drug targets, cellular pathways involved, biological processes, chemical compounds, and even scientific literature and clinical trial information. Due to this comprehensive knowledge base, the team conducting cancer research needed minimal adjustments to their analysis tools and UI.
The team chose to integrate their proprietary experimental data and enrich it with the Target Discovery Collection for enhanced target evaluation. Additionally, Ontotext integrated DepMap through their LinkedLifeData Inventory to further augment the target selection criteria.
Ontotext went beyond basic analysis by providing advanced metrics such as gene-disease association scores. These scores helped researchers understand the biological importance of potential targets and the strength of the evidence supporting them. Targets with higher scores were more likely to be relevant and have a stronger connection to the disease, making them better candidates for further investigation. Additionally, Ontotext used artificial intelligence to analyze scientific literature and clinical trials. This helped researchers assess how new and unexplored these targets were and confirm the link between the genes and the disease. This double-layered approach led to a more refined prioritization process.
Ontotext’s Target Discovery is like a Swiss Army Knife for drug discovery – it’s designed to be flexible and work for many different therapeutic areas. In this project, it was tailored to prioritize the most promising cancer targets. The UI was straightforward and user-friendly, allowing researchers to quickly test different ideas and adjust their search criteria as needed. This made the target selection process efficient and adaptable and reduced time spent on tedious jobs. By eliminating the manual steps of collecting the data for each target and assessing targets one by one, Target Discovery saved the team several months of research. This also provided a solid evidence-backed basis for critical decisions in their drug R&D journey.
The researchers feel that they have gained efficiencies in their prioritization of targets, and shared “All being available in one interface helps us to see the genes and proteins that are part of the research flow. And, most simply, it does what they said it would do. It does what we need it to do. What was big for us was the willingness of the Ontotext team to adjust the tool based on our needs. This relationship has been very big and positive for us.” ”
Business Benefits
- Streamlining and speeding up the screening process by a factor of 10: consolidate critical data and insights from multiple sources into a user-friendly system, featuring visual dashboards and analytical tools
- Efficient prioritization of targets: quickly and easily rank drug target candidates with higher therapeutic potential and confidence, tailored to specific cases
- Expertise-driven access: eliminate uncertainties in approaching various sources with specialized subject matter expertise
- Optimizing wet lab validation: simplify the shortlisting of potential successful candidates, expediting the validation process
- Accelerating decision-making: speed up target analysis and decision-making for faster research outcomes
Why Choose Ontotext
Ontotext’s Target Discovery is the ultimate research hub, seamlessly integrating crucial data and insights from diverse sources into a single, easy-to-manage platform. It simplifies the process of finding public information about genes, while also offering Ontotext’s in-depth analysis of their relevance to diseases and their novelty.
With the help of the platform, the global collaborative center’s team streamlined the prioritization of the most promising genes for lab investigation, optimizing time and resource allocation with a user-friendly ranking system. What previously took months of effort and resources can now be accomplished in a fraction of the time (often by just 1-2 people) eliminating the need to juggle multiple tools and databases, and delivering results significantly quicker.
