Recognizing and Celebrating Leaders in Innovation that Advance Life Science Research

Since 2003, Bio-IT World has hosted an elite awards program with the goal of highlighting outstanding examples of how technology innovations and strategic initiatives can be applied to advance life sciences research. This year’s winners represent excellence in innovation in the categories of Clinical & Health-IT, IT Infrastructure, Knowledge Management, and Personalized & Translational Medicine. Bio-IT World Conference & Expo.

Four grand prize awards were granted to AstraZeneca, Guardant Health with IQVIA, Merck KGaA, Darmstadt, Germany, with Genedata, and Quantum Leap Healthcare Collaborative with OpenClinica. We will recognize winners of the Innovative Practices Awards during the plenary keynote program on Tuesday, May 3 and hope you can join us for this premier event showcasing applications of IT and informatics to biomedical research and the drug discovery enterprise.

Augmented Drug Design

Anna Berg  ÅsbergAnna Berg Åsberg, Global Vice President R&D IT, AstraZeneca

The pharmaceutical industry is seeking to accelerate drug discovery through a renewed focus on the valuable data it has accumulated and find ways to use these data far more effectively through artificial intelligence and machine learning techniques that were previously impossible. Augmented Drug Design is the program driving AstraZeneca’s efforts in the drug design space with the aim of significantly reducing the time to develop candidate drugs. Built in conjunction with EPAM Systems, Amazon Web Services, and Schrödinger, the Augmented Drug Design platform uses centralized data access guided by FAIR data principles and high-performance computational modeling coupled with AI/ML insights to provide our scientists with novel drug design capabilities. In the twenty months since program inception, these technologies have been deployed against 70% of our small molecule projects and have significantly impacted several areas including molecular ideation, library design decisions, synthetic route planning, patent research and writing and have already contributed to accelerations in the discovery pipeline.

Learn more about this project during the team’s presentation in the Software Applications and Services track on Wednesday May 4, 3:40-4:10pm



Guardant Health nominated by IQVIA
Automating Biomarker and Phenotype Extraction With Natural Language Processing in a Real-World Precision Oncology Platform 

Irfan ShahIrfan Shah, Director, Business Development, Guardant Health

Paul MilliganPaul Milligan, PhD, Product & Strategy Director, IQVIA NLP

In the area of precision oncology, the more availability of high-quality clinical data that enables additional stratified insights to be gleaned, the better. This is the driving force behind an initiative by Guardant Health in partnership with IQVIA, Inc. to use state of the art text mining and Natural Language Processing (NLP) to structure and normalize complex clinical variables from clinical documents in the real-world clinical-genomic platform—Guardant INFORM. Built on Guardant360 liquid biopsy results, Guardant INFORM combines large volumes of genomic and clinical data to help accelerate research and development of next generation cancer therapeutics. Using NLP, key information such as TNM stage, biomarker profile, tumor histology, smoking history and performance status is now extracted from the patient narrative and transformed to normalized, structured data with precision of up to 100% for certain variables. By coupling deep phenotypic information with liquid biopsy results, more targeted drug development, better clinical trial optimization and more powerful post market research are all enabled.

Learn more about this project during the team’s presentation in the AI for Oncology, Precision Medicine, and Health track, Wednesday, May 4, 12:25-12:55pm.

Merck KGaA, Darmstadt, Germany nominated by Genedata
A Platform Democratizing Data, Analytics, and AI to Enable Development of Precision Therapies  

Marc  FleschMarc Flesch, PhD, Head, Dev, Genedata GmbH

Eike  StaubEike Staub, PhD, Senior Director/Head of Oncology Bioinformatics, Merck KGaA, Darmstadt, Germany

Precision medicine requires large interoperable datasets, high-performance analytics, and intense cross-functional collaboration for which digital technology is essential. This project highlights the value of an end-to-end big data platform for translational research, developed by Genedata AG in collaboration with Merck KGaA, Darmstadt, Germany. The platform supports all stages of drug R&D, from multi-omics NGS studies to digital pathology, from exploratory analyses for early drug research to statistics for late-stage clinical studies. We show how a data-driven culture can be supported by such a technical setup, through better data discoverability and sharing, thereby increasing research efficiency and productivity. We also demonstrate how secure cooperative work between internal and external expert analysts can be achieved: a key factor for leveraging the full potential of data. The presented solution, the outcome of a collaborative project, is today available as an off-the-shelf product, ready for other biopharma organizations. By enabling end-to-end automation of complex R&D workflows, high-performance analytics, and full data governance, the software allows companies to maximize the ROI of their R&D data to facilitate the development of next-generation precision therapies.

Learn more about this project during the team’s presentation in the Data Science & Analytics Technologies track on Thursday, May 5 10:25-10:55am.


Quantum Leap Healthcare Collaborative nominated by OpenClinica
OneSource Enables Automated EHR to eCRF Data Capture in Regulatory-Grade Clinical Trials 

Adam L.  AsareAdam L. Asare, PhD, Chief Data Officer, Quantum Leap Healthcare Collaborative; Director Of Information Technology, University of California San Francisco Medical Center

Cal  CollinsCal Collins, Co-Founder and CEO, OpenClinica

A major expense in clinical trials is the collection and abstraction of clinical data. This expense is further compounded by human errors that require additional investments in data cleaning/validation. Enhancements in the efficiency and accuracy of data capture are important advances in controlling the rising costs of clinical trials. We have established a flexible framework for integration and completion of Electronic Case Report Forms (eCRFs) through automated, direct capture from Electronic Health Record (EHR) systems. OneSource, launched within a participant’s EHR patient chart, automatically populates structured eCRFs by extracting data directly from the EHR, without need of manual abstraction. Deployed at eight clinical sites in the multicenter, adaptive phase 2 I-SPY-COVID-19 platform trial, we demonstrate a time savings of 61% over sites using manual data abstraction. Furthermore, at sites using OneSource, data errors were eliminated, leading to additional downstream cost savings in cleaning/validation costs. OneSource has the additional benefits of low implementation costs and reusability across sites.

Learn more about this project during the team’s presentation in the Digitization of Clinical Development and Clinical Trials track on Thursday, May 5, 12:25-12:55pm

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