HPE partners with biotech firm to advance precision medicine

Charlotte Edwards 27 November 2018 (Last Updated December 23rd, 2019 10:23)

Hewlett Packard Enterprise (HPE) has announced that it is collaborating with biotechnology and artificial intelligence (AI) startup company Jungla to create real-time personalised medical care for patients, as part of the Tech Impact 2030 project.

HPE partners with biotech firm to advance precision medicine
The company intends to apply its Memory-Driven Computing Sandbox to Jungla’s datasets. Credit: Hewlett Packard Enterprise Development LP.

Hewlett Packard Enterprise (HPE) has announced that it is collaborating with biotechnology and artificial intelligence (AI) startup company Jungla to create real-time personalised medical care for patients, as part of the Tech Impact 2030 project.

The company intends to apply its Memory-Driven Computing Sandbox to Jungla’s datasets with the aim of accelerating the clarity and utility of clinical genetic and genomic tests.

Advances in sequencing technologies have dramatically reduced the time and cost of genome sequencing, meaning personal genomes are becoming an affordable reality. Data from these genomes could give patients healthcare that is tailored towards their individual needs. It will also give researchers data to help them answer various genetic questions such as how a variation in genomes can affect the likelihood of a patient developing cancer or heart disease.

Less than 1% of genetic variants in the population are clinically understood and existing processes to interpret this information are heavily reliant on manual pattern recognition and correlation, which is said to slow down research and limit scalability.

Jungla CEO Carlos Araya said: “We firmly believe that to realise the value of genomic data, we need to look beyond changes in the sequence of a patient’s genome and into the changes induced to molecular and cellular function.

“To do this, we’ve built computational and experimental systems that can provide unprecedented levels of insight to clinical teams. This has required massive increases in the scale of data and the processes to generate and analyse it.”

Jungla’s Molecular Evidence Platform (MEP) has been designed to enable scientists to study the effects of variants on biological systems at scale and translate their insights into clinical practice. The integrated platform can provide interpretational support for findings in genetic and genomic tests.  As the MEP evolves, Jungla is integrating increasingly automated approaches to reveal how variations in the genome alter cells, such as cancer-causing DNA damage.

HPE fellow Michael Woodacre said: “With its unprecedented capacity to process data at scale, Memory-Driven Computing has allowed Jungla to use its analysis platform as a scientific instrument, reducing the risk of human error and dramatically speeding time to results.”

To aid the creation of Jungla’s genomic insights engine, HPE loaded Jungla’s data set onto its 48TB Memory-Driven Computing Sandbox, an operating and development environment. With this device, Jungla’s MEP can deliver approximately 250x speed improvements in high-resolution molecular analyses, when compared to traditional hardware.

Araya added: “Our work with HPE represents a commitment to push the envelope and bring advances in science and engineering to bear on the clinical tests of individual patients. Not only must we succeed at the science, we must build infrastructure and processes that can scale to translate scientific insights into clinical successes for patients.

“HPE’s Memory-Driven Computing systems can allow us to consider new findings from a patient in the context of the molecular characteristics of all clinically understood variants, on demand. These developments don’t happen overnight, but it’s where we need to go if we want to enable both speed and accuracy in healthcare.”

HPE’s Tech Impact 2030 programme is intended to solve societal challenges in key industries such as agriculture, financial services, healthcare, transportation and manufacturing.