Disease Studies

Delivering personalized dietary advice for health management and disease prevention

Background and Objectives: Diet plays a huge role in health, both by increasing metabolic disease risks and acutely through adverse interactions with diseases and medications. Multimorbid and polypharmaceutical patients are at a particularly high risk of such interactions due to the number of drugs they take. This leads to avoidable hospitalizations and poor compliance. This study built and demonstrated a tool that provides personalized dietary advice that accounts for a patient’s combination of disease and drugs in real‑time on their mobile device.

Methods: A comprehensive list of validated drug‑disease‑food interactions from several reputable sources was constructed. This was compiled into a knowledge graph using the RACE array logic platform. This interactions knowledge graph was used to power a personalized dietary advisor application on a mobile device.

Results: Data from over 500,000 drug‑disease‑food interactions including 1,699 food ingredients and 9,526 disease interactions were compiled into a highly compressed knowledge model. This was used to inform recommendations for individual complex patients. It was also tested on virtual population of 10,000 multimorbid and polypharmaceutical patients.

Conclusions: This study showed that digital health tools can provide highly contextual and adaptive responses from a single knowledge graph. The study showed it is possible to provide highly personalized health advice to complex patients in real‑time on their own mobile device without having to hold such private information on a server. This enables highly secure, private and personalized digital health tools to be built.

To view the publication in full, please see https://www.digitmedicine.com/article.asp?issn=2226-8561;year=2018;volume=4;issue=3;spage=127;epage=132;aulast=Gardner#



More News & Media

View All News & Media

Combinatorial analytics: An essential tool for the delivery of precision medicine and precision agriculture

An Opinion, published in the new Open Access Journal Artificial Intelligence in the Life Sciences from Elsevier, describes the…

31/05/21
Read more

Combinatorial analysis of phenotypic and clinical risk factors associated with hospitalized COVID-19 patients

A study using de-identified clinical claims and labs data for US COVID-19 patients. We replicated previous findings around the…

25/02/21
Read more

The COVID-19 PHARMACOME: Rational Selection of Drug Repurposing Candidates from Multimodal Knowledge Harmonization

The SARS-CoV-2 pandemic has challenged researchers at a global scale. The scientific community’s massive response has resulted in a…

26/05/21
Read more

Keep in touch

Please enter your email address if you would like to be kept informed of our work here at PrecisionLife. Note that our Privacy Policy and Terms & Conditions apply.

  • This field is for validation purposes and should be left unchanged.

Contact us

If you have any questions or would like to speak to us in terms of potential collaborations or partnership opportunities, please get in touch using the form below or email info@precisionlife.com and we will get back to you as soon as we can. Note that our Privacy Policy and Terms & Conditions apply.


UK

Unit 8b Bankside
Hanborough Business Park
Long Hanborough, OX29 8LJ

USA

1 Broadway Fl 14
Cambridge
MA 02142-1187

Denmark

Agern Allé 3
DK-2970
Hørsholm

Poland

CIC Ul
Chmielna 73m
00-801 Warszawa

  • This field is for validation purposes and should be left unchanged.