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Laying the foundations for effective AI implementations [Webinar]
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Life science processes, be it in research, drug discovery, development, manufacturing, or diagnostic test development and execution, have grown in complexity and scale, not the least because the industry is facing ongoing pressures such as ROI challenges.

Logo - L7 Informatics

This rapid growth has resulted in disconnected and suboptimal laboratory process management systems and the lack of a unified data strategy that would provide the necessary laboratory and business process insights with the potential to shorten the overall product life cycle.

In parallel, the industry is heavily investing in modernizing data infrastructures and, more recently, in AI capabilities to derive insights from the rapidly growing volumes of data generated. While the promise of AI is huge, what is often overlooked when implementing generative AI and predictive AI models is the foundation of data on which AI is based and used.

To derive high-value insights from an AI model requires removing data silos and applying an enterprise-wide data standard. The L7 Informatics and SciBite partnership offers the solution to these requirements. As contextualized data is collected during process orchestration within the Unified L7|ESP platform, the integration with SciBite’s CENtree platform facilitates the alignment of the data collected to enterprise data standards and public ontologies.

During this webinar, we will outline the synergies between L7 Informatics and SciBite and how an integration of our respective platforms, support our mutual customers in preparing their data to fully exploit the power of AI.

Presenter(s): 

  • Vasu Rangadass, Ph.D. Chief Executive Officer at L7 Informatics
  • Alfredo Coviello, Product Development and Engineering at L7 Informatics
  • Sam Shelton, Ph.D., Director of Alliances at SciBite
  • Harpreet Singh Riat, Director of Technical Sales at SciBite

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Headshot - Sam Shelton
Sam Shelton
Director of Alliances, SciBite

Sam leads partnerships and alliances at SciBite, working collaboratively with existing partners and developing new partnerships aligned to SciBite’s strategic goals. He has a strong technical background in the life sciences, with a PhD in Protein Biochemistry from the University of Nottingham and post-doctoral training in bioinformatics within the department of Neurosurgery at the University of California San Francisco.

Prior to Joining SciBite he held technical sales and commercial roles at Carl Zeiss and most recently led business development at Repositive, building relationships with contract research organisations, biotech’s and pharma companies, facilitating data exchange and search across multiomic datasets. He has a good grasp of the challenges of dealing with unstructured scientific data, and collaboratively developing practical solutions to overcome these.

Headshot - Zahra Hosseini
Zahra Hosseini
Senior Data Scientist, SciBite

Zahra Hosseini, Senior Data Scientist. Holds a Ph.D. in machine learning from the Science and Research University of Tehran, focusing on Natural Language Processing (NLP) and knowledge discovery. She was an Assistant professor at Azad University of Isfahan for 7 years before switching to Industry. She has been with SciBite since 2021 as a part of the data science team.

Other articles by Zahra

  1. How SciBite and Elsevier manage KOL identification read more.
  2. How SciBite technology can facilitate gene-disease relationship extraction read more.
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