Accelerating early-stage and clinical drug development

 

Since 2016, the biotechnology industry has faced unprecedented uncertainty in both Europe and the United States with new competition coming from China and tech-giants. in order to stay ahead Biotech companies will need to leverage and incorporate emerging digital technologies into their R&D processes or be replaced by those who do. Access to relevant insights, both real time and even faster is imperative if you want to stay innovative and make novel discoveries in less time. Innoplexus’ technology empowers biotechs with an automated search in the biggest life science data ocean consisting of over 95% of publicly available data. To the point of access to applicable life science data allows biotechs to generate faster insights, discover new connections between biological entities and also identify KOLs – on a fingertip. This would help the industry save both time and costs.

ONTOSIGHT® Discover: AI-based discovery engine for more accurate real-time insights

The Ontosight® Discover platform for life sciences harnesses artificial intelligence (AI) to provide fully automated concept-based search on publicly available data from sources such as publications, congresses, clinical trials, etc. Ontosight® enriches and continually analyses data by means of our proprietary life sciences ontology. Our ontology establishes relationships between biological entities such as genes, proteins, diseases, and drugs, helping to contribute to the discovery of new connections. The user gets real-time updates and notifications.

 

Ontosight® Discover is designed to enrich and accelerate the research processes and decision-making. As a web-based platform, no installation is required so getting started is as simple as receiving your login.

 

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Innoplexus’ AI–powered Solutions

Access over 95% of the world’s life sciences data through Innoplexus’ discovery engine, which is powered by a proprietary life sciences-specific ontology. The ontology empowers users to perform context-based rather than keyword searches, and generate insights faster.

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Leverage Innoplexus’s life sciences data ocean, which encompasses over 95% of all publicly available data, to discover novel therapies by identifying the connections and interactions between closely and distantly related genes, pathways, molecular targets, and drugs.

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Predict and optimize toxicity properties of molecules by leveraging a machine learning approach to Quantitative Structure-Activity Relationship (QSAR).

Predict-Molecule-Toxicology

Leverage the power of artificial intelligence and Innoplexus’s life sciences data ocean, to validate the biological activity of new molecular entities and determine druggability scores.

Biological-Activity

Use Innoplexus’ full capabilities, including identifying connections between biological entities, predicting toxicologies, validating the biological activity of new molecules, estimating clinical trial costs, and assessing the competitive landscape to determine drug assets most likely to demonstrate efficacy, safety, and commercial success.

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Utilize Innoplexus’s patent and grant landscape capabilities to find opportunities for drug development and funding. Search for patents in specific therapeutic areas and countries to gain market and competitor insights. Access available grants to find relevant funding sources.

early-stage-drug-development

Identify new opportunities for assets languishing on-the-shelf or approved drugs by leveraging Innoplexus’s life sciences data ocean and ontologies to identify new indications. Additionally, gain insights into pathways that can be targeted with already developed mechanisms of action.

Drug-Repurposing

Leverage Innoplexus’ life sciences data ocean, which encompasses over 95% of all publicly available data, to discover novel therapies by identifying the connections and interactions between closely and distantly related genes, pathways, molecular targets, and drugs.

Discover-Novel-Therapies

Access untapped KOL networks. Identify Top vs. Emerging KOLs and filter them by therapeutic area, location, publications, clinical trials, relationships with pharmaceutical competitors, and numerous customizable filters. Determine which KOLs to engage with based on four KOL archetypes Innoplexus has identified: Commercial, Clinical, Thought-leaders, and Public Speakers.

clinically-oriented-KOLs

Identify and select clinical trial sites based on site’s involvement in past trials by drug phase and indication, number of associated scientific KOL, proximity to patient populations, and hospital features (departments present, hospital beds, etc.).

Clinical-Trial-Sites

Accelerate the development of robust clinical trials by quickly comparing trials from over 100+ databases, including clinicaltrials.gov. Connect the outcomes of clinical trials, such as progression to subsequent phases, regulatory approval, and payer decisions with the trial parameters such as trial duration, sample sizes, endpoints, inclusion / exclusion criteria, and others to determine the optimal trial design.

Clinical-Trial-Design

Case studies & capabilities

Pipeline Prioritization

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Site Optimization & Enrollment

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Endotype Response & Personalized Medicine

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CONTINUOUSLY-UPDATING PIPELINE PRIORITIZATION PLATFORM

  • Biological Validation: Identifying and validating potential uses of target, pathway, disease and drug candidates
  • Clinical Trial Valuation: Estimating costs of clinical trials and likelihood of success
  • Commercial Evaluation: Monitoring competitors and determining commercial opportunity

DETERMINING ENDOTYPE RESPONSE & STRATIFYING PATIENTS

  • Optimizing clinical trial patient selection by stratificating patients based on predicted levels of response to therapy
  • Connecting endotype responses to published literature and clinical trial data
  • Continually integrating new data streams to update endotype response predictions

OPTIMIZING CLINICAL TRIAL DESIGN & SITE ENROLLMENT

  • Assessing all past and ongoing clinical trials and drugs’ regulatory approval
  • Identifying and prioritizing clinical trial sites based on a multitude of parameters
  • Identifying top or emerging Key Opinion Leaders for clinical trial involvement

Experience more Aha! Moments

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