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27

Mar 24

Partex NV announces collaboration with Althea DRF Lifesciences to provide comprehensive end-to-end services to accelerate drug discovery and development

Frankfurt, Germany; 28 March 2024 – Partex Group, a pioneer in AI-driven drug discovery, announces a collaboration with Althea DRF...
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18

Mar 24

Innovative AI technology in oncology: Partex Group presents results from a pilot project

During the German Cancer Congress 2024 in Berlin, the companies Innoplexus AG /Amrit AG, companies of Partex N.V., presented the...
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Innoplexus wins Horizon Interactive Gold Award for Curia App

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Innoplexus in Nvidia GPU technology conference 2019

Gaurav

Gaurav Tripathi
CTO – Innoplexus

Speaker Bio

Gaurav is CTO of Innoplexus AG, where he leads technology and innovation efforts and has been instrumental in developing new technologies and products. He has more than 13 years of experience in big data and analytics, search, ontologies, computer vision, machine learning, artificial intelligence, and natural language processing. During his career, he’s helped large organizations and startups get an edge on technology and product development and scale quickly. He has filed a number of patents and is exploring the emerging technology landscape around AI and Blockchain. Gaurav founded his first technology company at age 19 while attending IIT Bombay to bundle the innovative forces across all IITs.

Session Description

How To Use GPUs For Faster, Better and Cheaper Drug Development

We’ll demonstrate how different kinds of AI techniques can be used across all four stages of drug development — preclinical, clinical, regulatory, and commercial. Each stage requires a huge volume of mostly unstructured data that must be analyzed to generate insights. We’ll provide several examples of our methods, including using GPUs to accelerate segmentation and image processing in information extraction from PDFs, HTML files, and images combining CNN and LSTM. Other examples include using GPUs to accelerate training to identify biomedical entities and resolve them to correct type with a combination of CRF and RNN. We’re also using GPUs to accelerate graph traversals in mapping connections among millions of biomedical concepts in real time.

Additional Information

PRIMARY SESSION TOPIC: Healthcare – Informatics/Real World Evidence
ALL TOPICS: AI/Deep Learning Business Track (High Level), Healthcare – Informatics/Real World Evidence
INDUSTRY SEGMENTS: Healthcare & Life Sciences
TECHNICAL LEVEL: Business/Executive level
SESSION TYPE: Talk
SESSION LENGTH: 50 minutes

vatsal

Vatsal Agarwal
Vice President – Technology & Innovation, Innoplexus Consulting Services Pvt. Ltd.

Speaker Bio

Vatsal leads the innovation team at Innoplexus, building cutting-edge technology for the pharmaceutical and life sciences industries. He works on the life sciences language-processing engine and the domain-wide ontology used in the company’s iPlexus platform. Vatsal has more than 10 years of experience in data science, software development, and bioinformatics. His primary focus is to bring advancements in artificial intelligence and big data to life sciences to help patients get faster, more efficient treatments. Vatsal has filed over 35 patent applications and written several peer-reviewed publications on machine learning and bioinformatics.

Session Description

Real-Time Connection-Based Filtering to Improve the Precision of the Search Engine in Life Sciences

We’ll talk about how we built a GPU-Accelerated system for real-time information retrieval from large datasets in life sciences. Unstructured textual data is full of phrases and words that have multiple meanings, making it difficult for current information-retrieval algorithms to find relevant documents. We’ll describe our knowledge graph-based filtering mechanism for more precise real-time information retrieval. We outline how we accelerated the embedding generation process, treating it as an optimization problem and running it on NVIDIA Tesla V100 GPU cores. We’ll also cover how we reduced the latency in distance computation using TensorRT.

Additional Information

PRIMARY SESSION TOPIC: AI Application Deployment/Inference
ALL TOPICS: Deep Learning – Speech/Language Processing, AI Application Deployment/Inference
INDUSTRY SEGMENTS: Healthcare & Life Sciences
TECHNICAL LEVEL: Intermediate technical
SESSION TYPE: Talk
SESSION LENGTH: 50 minutes

This Event originally published on Nvidia.