Mathematical Modeling of Andrographolide Therapy Effects and Immune Response in In Vivo Dynamics of SARS-CoV-2 Infection
บทความในวารสาร
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Panittavee Yarnvitayalert and Teerapol Saleewong
ผู้เผยแพร่: MDPI
ปีที่เผยแพร่ (ค.ศ.): 2025
Volume number: 17
Issue number: 891
หน้าแรก: 1
หน้าสุดท้าย: 16
จำนวนหน้า: 16
นอก: 19994915
eISSN: 1999-4915
บทคัดย่อ
This study explores the viral dynamics of SARS-CoV-2 infection within host cells by incorporating the pharmacological effects of andrographolide—a bioactive compound extracted from Andrographis paniculata, renowned for its antiviral, anti-inflammatory, and
immunomodulatory properties. Through the application of mathematical modeling, the
interactions among the virus, host cells, and immune responses are simulated to provide a
comprehensive analysis of viral behavior over time. Two distinct models were employed to
assess the impact of varying andrographolide dosages on viral load, target cell populations,
and immune responses. One model revealed a clear dose–response relationship, whereas
the other indicated that additional biological or pharmacological factors may modulate
drug efficacy. Both models demonstrated stability, with basic reproductive numbers (R0)
suggesting the potential for viral propagation in the absence of effective therapeutic interventions. This study emphasizes the significance of understanding the pharmacokinetics
(PK) and pharmacodynamics (PD) of andrographolide to optimize its therapeutic potential.
The findings also underscore the necessity for further investigation into the compound’s
absorption, distribution, metabolism, and excretion (ADME) characteristics, as well as
its prospective applications in the treatment of not only COVID-19 but also other viral
infections. Overall, the results lay a foundational framework for future experimental research and clinical trials aimed at refining andrographolide dosing regimens and improving
patient outcomes.
คำสำคัญ
Andrographolide, COVID-19, Mathematical modeling, pharmacokinetic, viral dynamic model