Harnessing Artificial Intelligence to Optimize Long‐Term Maintenance Dosing for Antiretroviral‐Naive Adults with HIV‐1 Infection. Issue 4 (11th November 2019)
- Record Type:
- Journal Article
- Title:
- Harnessing Artificial Intelligence to Optimize Long‐Term Maintenance Dosing for Antiretroviral‐Naive Adults with HIV‐1 Infection. Issue 4 (11th November 2019)
- Main Title:
- Harnessing Artificial Intelligence to Optimize Long‐Term Maintenance Dosing for Antiretroviral‐Naive Adults with HIV‐1 Infection
- Authors:
- Shen, Yinzhong
Liu, Tingyi
Chen, Jun
Li, Xin
Liu, Li
Shen, Jiayin
Wang, Jiangrong
Zhang, Renfang
Sun, Meiyan
Wang, Zhenyan
Song, Wei
Qi, Tangkai
Tang, Yang
Meng, Xianmin
Zhang, Lijun
Ho, Dean
Ho, Chih‐Ming
Ding, Xianting
Lu, Hong‐Zhou - Abstract:
- Abstract: Antiretroviral therapy (ART) serves as a mainstay in treating human immunodeficiency virus (HIV) infection. An HIV patient is traditionally administered the same ART regimen for life, even if his/her viral load has been reduced by several orders of magnitude from the initial viral load. Dose reduction in ART has been clinically explored in a trial‐and‐error manner to reduce side effects and improve ART sustainability. Using artificial intelligence (AI), we have discovered that drugs and doses inputs can be related to viral load reduction through a Parabolic Response Surface (PRS). The AI‐PRS platform can rationally guide a clinically‐actionable approach to identify optimized population‐wide and personalized dosing. In this prospective pilot clinical trial, a combination regimen of tenofovir (TDF), efavirenz (EFV) and lamivudine (3TC) is administered to ten patients. Using AI‐PRS, a 33% reduction in the long‐term TDF maintenance dose (200 mg) is identified compared to standard regimens (300 mg). This regimen keeps the HIV viral load below 40 copies/mL with no relapse during a 144‐week observation period. This study demonstrates that AI‐PRS can potentially serve as a scalable approach to optimize and sustain the long‐term management of HIV as well as a broad spectrum of other indications. Abstract : Lifetime antiretroviral therapy (ART) is crucial for HIV/AIDS patients. To find a balance between the ART side effects and the risk of relapse, this prospective pilotAbstract: Antiretroviral therapy (ART) serves as a mainstay in treating human immunodeficiency virus (HIV) infection. An HIV patient is traditionally administered the same ART regimen for life, even if his/her viral load has been reduced by several orders of magnitude from the initial viral load. Dose reduction in ART has been clinically explored in a trial‐and‐error manner to reduce side effects and improve ART sustainability. Using artificial intelligence (AI), we have discovered that drugs and doses inputs can be related to viral load reduction through a Parabolic Response Surface (PRS). The AI‐PRS platform can rationally guide a clinically‐actionable approach to identify optimized population‐wide and personalized dosing. In this prospective pilot clinical trial, a combination regimen of tenofovir (TDF), efavirenz (EFV) and lamivudine (3TC) is administered to ten patients. Using AI‐PRS, a 33% reduction in the long‐term TDF maintenance dose (200 mg) is identified compared to standard regimens (300 mg). This regimen keeps the HIV viral load below 40 copies/mL with no relapse during a 144‐week observation period. This study demonstrates that AI‐PRS can potentially serve as a scalable approach to optimize and sustain the long‐term management of HIV as well as a broad spectrum of other indications. Abstract : Lifetime antiretroviral therapy (ART) is crucial for HIV/AIDS patients. To find a balance between the ART side effects and the risk of relapse, this prospective pilot clinical study harnesses the parabolic response surface, an artificial intelligence platform, to identify a personalized optimal ART dose. With it, all patients get viral suppression with no relapse during a 144‐week observation period. … (more)
- Is Part Of:
- Advanced therapeutics. Volume 3:Issue 4(2020)
- Journal:
- Advanced therapeutics
- Issue:
- Volume 3:Issue 4(2020)
- Issue Display:
- Volume 3, Issue 4 (2020)
- Year:
- 2020
- Volume:
- 3
- Issue:
- 4
- Issue Sort Value:
- 2020-0003-0004-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2019-11-11
- Subjects:
- artificial intelligence -- drug therapy -- human immunodeficiency virus
Therapeutics -- Periodicals
Pharmaceutical technology -- Periodicals
Pharmacogenetics -- Periodicals
615.5 - Journal URLs:
- https://onlinelibrary.wiley.com/loi/23663987 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/adtp.201900114 ↗
- Languages:
- English
- ISSNs:
- 2366-3987
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.935580
British Library DSC - BLDSS-3PM
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- 13251.xml