Cargando…

Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine

Many current clinical therapies for chronic diseases involve administration of drugs using dosage and bioavailability parameters estimated for a generalized population. This standard approach carries the risk of under dosing, which may result in ineffective treatment, or overdosing, which may cause...

Descripción completa

Detalles Bibliográficos
Autores principales: Stefanov, Bozhidar-Adrian, Fussenegger, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548536/
https://www.ncbi.nlm.nih.gov/pubmed/36225597
http://dx.doi.org/10.3389/fbioe.2022.986210
_version_ 1784805450617716736
author Stefanov, Bozhidar-Adrian
Fussenegger, Martin
author_facet Stefanov, Bozhidar-Adrian
Fussenegger, Martin
author_sort Stefanov, Bozhidar-Adrian
collection PubMed
description Many current clinical therapies for chronic diseases involve administration of drugs using dosage and bioavailability parameters estimated for a generalized population. This standard approach carries the risk of under dosing, which may result in ineffective treatment, or overdosing, which may cause undesirable side effects. Consequently, maintaining a drug concentration in the therapeutic window often requires frequent monitoring, adversely affecting the patient’s quality of life. In contrast, endogenous biosystems have evolved finely tuned feedback control loops that govern the physiological functions of the body based on multiple input parameters. To provide personalized treatment for chronic diseases, therefore, we require synthetic systems that can similarly generate a calibrated therapeutic response. Such engineered autonomous closed-loop devices should incorporate a sensor that actively tracks and evaluates the disease severity based on one or more biomarkers, as well as components that utilize these molecular inputs to bio compute and deliver the appropriate level of therapeutic output. Here, we review recent advances in applications of the closed-loop design principle in biomedical implants for treating severe and chronic diseases, highlighting translational studies of cellular therapies. We describe the engineering principles and components of closed-loop therapeutic devices, and discuss their potential to become a key pillar of personalized medicine.
format Online
Article
Text
id pubmed-9548536
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-95485362022-10-11 Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine Stefanov, Bozhidar-Adrian Fussenegger, Martin Front Bioeng Biotechnol Bioengineering and Biotechnology Many current clinical therapies for chronic diseases involve administration of drugs using dosage and bioavailability parameters estimated for a generalized population. This standard approach carries the risk of under dosing, which may result in ineffective treatment, or overdosing, which may cause undesirable side effects. Consequently, maintaining a drug concentration in the therapeutic window often requires frequent monitoring, adversely affecting the patient’s quality of life. In contrast, endogenous biosystems have evolved finely tuned feedback control loops that govern the physiological functions of the body based on multiple input parameters. To provide personalized treatment for chronic diseases, therefore, we require synthetic systems that can similarly generate a calibrated therapeutic response. Such engineered autonomous closed-loop devices should incorporate a sensor that actively tracks and evaluates the disease severity based on one or more biomarkers, as well as components that utilize these molecular inputs to bio compute and deliver the appropriate level of therapeutic output. Here, we review recent advances in applications of the closed-loop design principle in biomedical implants for treating severe and chronic diseases, highlighting translational studies of cellular therapies. We describe the engineering principles and components of closed-loop therapeutic devices, and discuss their potential to become a key pillar of personalized medicine. Frontiers Media S.A. 2022-09-26 /pmc/articles/PMC9548536/ /pubmed/36225597 http://dx.doi.org/10.3389/fbioe.2022.986210 Text en Copyright © 2022 Stefanov and Fussenegger. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Stefanov, Bozhidar-Adrian
Fussenegger, Martin
Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine
title Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine
title_full Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine
title_fullStr Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine
title_full_unstemmed Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine
title_short Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine
title_sort biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9548536/
https://www.ncbi.nlm.nih.gov/pubmed/36225597
http://dx.doi.org/10.3389/fbioe.2022.986210
work_keys_str_mv AT stefanovbozhidaradrian biomarkerdrivenfeedbackcontrolofsyntheticbiologysystemsfornextgenerationpersonalizedmedicine
AT fusseneggermartin biomarkerdrivenfeedbackcontrolofsyntheticbiologysystemsfornextgenerationpersonalizedmedicine