nference | Collaborations for Pharma

Collaborations for Life Sciences

Our scientists use the nference platform and data in collaboration with your teams to tackle your most important questions and challenges

nference is creating the largest labeled EMR dataset in healthcare

EMR data contains longitudinal real-world, “deep data” rich in clinical phenotypes and outcomes spanning across therapeutic ares, but exists in in largely semi-structured and unstructured form. The nference platform powers the tranformation of the raw data into a labeled EMR dataset.

HARMONIZATION

We leverage our deep biomedical expertise to transform semi-structured data (e.g. lab tests, procedures) into structured data through technology-enabled data harmonization.

AUGMENTED CURATION

We build upon state-of-the-art neural networks and Natural Language Processing (NLP) methods to transform unstructured clinical text (e.g. clinical notes...) into structured patient features.

BIOPHARMA COLLABORATIONS

Triangulation across data and state of the art algorithms power collaborations

Connecting structured, harmonized EMR data with publicly available literature, molecular and real world datasets and applying our powerful proprietary algorithms allows us to ask and answer challenging questions

Triangulation with public and proprietary data1

Integrating additional data sources with labeled, curated and harmonized EMR data can strengthen the insights derived from downstream data analysis. This data includes biomedical literature (ex. PubMed), clinical trials (ex. clinicaltrials.gov) and molecular data (ex. Gene Expression Omnibus).

State of the art algorithms

The labeled, curated and harmonized EMR data serves as a starting point that enables training state-of-the-art AI algorithms. We develop these algorithms as solutions to some of the major challenges in healthcare, including early detection and diagnosis of disease, identification of biomarkers for disease progression and more.

NFERENCE COLLABORATIONS FOR BIOPHARMA

Work with our scientists to tackle hard problems in Pharma R&D, Medical Affairs and Strategy

Our scientists will use the nference platform and data in collaboration with your teams to tackle the questions and challenges most important to you

Target discovery

Identify candidate targets with significant evidence for potential therapeutic benefit for a selected indication

Lifecycle Management

Evaluate likelihood of drug success pre-launch and identify opportunities for commercialized assets

Clinical Trial Design

Build complex patient cohorts using real world EMR data to optimize clinical study criteria and study design.

Real World Outcomes

Track patient-level outcomes following specific treatments or interventions

Precision Medicine

Identify biomarkers or correlates of disease progression or treatment outcomes using our clinico-genomic data which spans therapeutic areas

Early Intervention

Identify indicators of disease or disease progression to support earlier, targeted treatment or intervention

Early Diagnosis

Leverage the longitudinality of our dataset and power of our technology to identify early predictors of disease

Drug Toxicity

Identify drug side effects and understand the populations most susceptible to them based on real world use

Symptoms

Identify disease symptoms and understand the populations most susceptible to them

Patient Journey

Get disease area specific insight on the end-to-end patient journey, leveraging longitudinal patient data