Technology

We are a team of bioinformaticians, developers, biophysical chemists and computer scientists, and collaborate with research focused medical schools in specific disease areas. Our principal focus is to discover drug repurposing candidates using AI and data analytic techniques, and perform primary experimental validations.

Ligand-Protein Interaction Site Characteristics used to Generate Repurposing Opportunities

We have predicted several high-probability ligand-target pairs using novel, hybrid sequence/structure based pattern matching studies. Using a combination of database integration and computational modeling, the algorithm focuses on the binding characteristics of the compound. Hits are constantly generated based on subjective constraints based on search and optimization techniques.

Data Integration as a Source for Repurposing Hypothesis

We integrate data using big data technologies to develop repurposing strategies based on specific chemical and biological mechanisms.
We plan to develop this further by directly partnering with pharmaceutical companies to guide their discovery/development activities of both in-trial candidates and as an integrated part of the discovery pipeline to make intelligent choices for advancing leads to trials. 

AI targeting a staggered thematic integration

The development of data focused pipelines in a quest for new clinical successes can greatly be advanced by AI-focused algorithms. The integration of data and the related predictions are based on direct associations. It lacks the ability to discover drug-target interactions that have no known associations. This is where AI techniques contribute. The goal here is to develop predictive modeling platforms based on AI technologies to identify the entities that are most correlated to true positives. 

Mission

We focus on development tracks that have novel strategies to aggregate bioinformatics data. It is well known that data points are more expensive to generate in the field of pharma and therefore as a general principle, we would like to integrate data resources additively.
We have seen some success in our initial work with prototype models that use multi-source data additively as a substitute to volume.
In summary, rather than using only established and specific themes to explore repurposing strategies, we are in the process of integrating various key contributors to drug binding to predict repurposed hypotheses. 

About Us

Mobirise

Prashanth Athri, PhD

Co-Founder

Dr. Prashanth Athri is the founding member of CubeBio AI. He focuses on the development, innovation and prototype implementation of the AI-based platform for drug discovery at CubeBio. He has worked at Strand Life Sciences, Bengaluru as a Senior Specialist (bioinformatics data analytics), and has held post-doctoral fellowships EPF Lausanne, Switzerland & Emory University, Atlanta, USA. He received his Ph. D. in Computational Chemistry and Bioinformatics (minor) at Georgia State University, preceded by M. S. in Computer Science and Bioinformatics (minor). His research interests include the application of AI to drug discovery, and it’s interplay with semantic integration of X-omic data towards identifying novel insights in the area of drug-target interactions

Madhura Purnaprajna

Madhura Purnaprajna

Co-Founder

Dr.-Ing. Madhura Purnaprajna will co-drive the acceleration of AI algorithms across multiple hardware architectures along with Dr. Mario Porrmann and Jens Hagmeyer. She was the recipient of two prestigious post-doctoral fellowships: an International Research Fellowship from the German Research Foundation (Deutsche Forschungsgemenischaft) and Swiss National Science Foundation’s Marie Heim-Vögtlin fellowship. These fellowships grants were implemented at the Processor Architecture Lab, EPFL, Switzerland and the High Performance Computing Lab, IISc., Bangalore. Her research interests are in Reconfigurable Computing and Processor Architectures. She received her PhD in Electrical Engineering from the Heinz Nixdorf Institute, University of Paderborn, Germany. She has a Master's degree from the University of Alberta, Canada. Before that, she spent about 4 years in the Indian Semiconductor Industry.


ParaXent GmbH

Co-developers and Equity partners of CubeBioAI

Dr.-Ing Mario Porrmann and Jens Hagemeyer are co-founders of ParaXent GmbH, a spin-off targeting the development of highly scalable FPGA systems for rapid prototyping and high performance computing. The team, which will be bridged by Dr. Purnaprajna, will contribute to accelerating various AI algorithms for drug discovery, through the use of a novel scalable compute platform for high-performance computing (HPC) using heterogeneous devices such as CPUs, GPUs and FPGAs, combined with a flexible, low-latency communication infrastructure


Mario Porrmann

Mario Porrmann

Founding team member

Prof. Dr.-Ing. Mario Porrmann is head of the Computer Engineering group at Osnabrück University. He graduated as "Diplom-Ingenieur" in Electrical Engineering at the University of Dortmund, and a PhD in Electrical Engineering from the University of Paderborn in 2001.He has served various academic faculty levels and is now Academic Director of Center of Excellence Cognitive Interaction Technology at Bielefeld University.

ParaXent GmbH

Jens Hagemeyer

Founding team member

Jens Hagemeyer received his degree in electrical engineering combined with computer science at the University of Paderborn, Germany, and the diploma degree from the University of Paderborn, in 2006. He researches in the area of FPGA-centric system design, design of dynamically reconfigurable systems and resource-efficient computer architectures.


D. Jawahar

D. Jawahar

Angel Investor

Prof. Jawahar Doreswamy is currently the CEO and Pro Chancellor at PES University. He has provided the initial funding, access to world-class infrastructure at PES University’s incubation facility, and is a Board member of CubeBio AI. He has a graduate degree from Texas A & M. He has spearheaded the development of PES University for 3 decades, and steered it to being the No. 1 Engineering Institute in Karnataka, IN.


Prof. Donald Hamelberg

Scientific Advisor

Professor, Biophysical Chemistry, Georgia State University, Atlanta Dr. Hamelberg will advise us on allosteric network characterization and modelling. He has extensive experience and has been a prolific contributor to top journals in Chemistry in this area. We consider him to be core to driving the molecular dynamics/ biophysical chemistry aspects of scientific development activities.

His PhD and post-doctoral experience has been from Georgia State, University of Illinois, Howard Hughes Institute and UCSD.

Prof. Gowri Srinivasa

Scientific Advisor

Professor, Computer Science, PES University, Bangalore Dr. Srinivasa will guide and advise the AI aspects of the company’s efforts. She has extensive experience in applying AI to various biomedical domains.

Her PhD is from Carnegie Mellon University.


Mobirise

Contact us

#617 Pixel Park

PESIT South Campus Incubation Center

Bengaluru - 560100