Quantitative systems pharmacology model of the amyloid pathway in Alzheimer's disease: Insights into the therapeutic mechanisms of clinical candidates. (6th November 2022)
- Record Type:
- Journal Article
- Title:
- Quantitative systems pharmacology model of the amyloid pathway in Alzheimer's disease: Insights into the therapeutic mechanisms of clinical candidates. (6th November 2022)
- Main Title:
- Quantitative systems pharmacology model of the amyloid pathway in Alzheimer's disease: Insights into the therapeutic mechanisms of clinical candidates
- Authors:
- Ramakrishnan, Vidya
Friedrich, Christina
Witt, Colleen
Sheehan, Robert
Pryor, Meghan
Atwal, Jasvinder K.
Wildsmith, Kristin
Kudrycki, Katherine
Lee, Seung‐Hye
Mazer, Norman
Hofmann, Carsten
Fuji, Reina N.
Jin, Jin Y.
Ramanujan, Saroja
Dolton, Michael
Quartino, Angelica - Abstract:
- Abstract: Despite considerable investment into potential therapeutic approaches for Alzheimer's disease (AD), currently approved treatment options are limited. Predictive modeling using quantitative systems pharmacology (QSP) can be used to guide the design of clinical trials in AD. This study developed a QSP model representing amyloid beta (Aβ) pathophysiology in AD. The model included mechanisms of Aβ monomer production and aggregation to form insoluble fibrils and plaques; the transport of soluble species between the compartments of brain, cerebrospinal fluid (CSF), and plasma; and the pharmacokinetics, transport, and binding of monoclonal antibodies to targets in the three compartments. Ordinary differential equations were used to describe these processes quantitatively. The model components were calibrated to data from the literature and internal studies, including quantitative data supporting the underlying AD biology and clinical data from clinical trials for anti‐Aβ monoclonal antibodies (mAbs) aducanumab, crenezumab, gantenerumab, and solanezumab. The model was developed for an apolipoprotein E ( APOE ) ɛ4 allele carrier and tested for an APOE ɛ4 noncarrier. Results indicate that the model is consistent with data on clinical Aβ accumulation in untreated individuals and those treated with monoclonal antibodies, capturing increases in Aβ load accurately. This model may be used to investigate additional AD mechanisms and their impact on biomarkers, as well as predictAbstract: Despite considerable investment into potential therapeutic approaches for Alzheimer's disease (AD), currently approved treatment options are limited. Predictive modeling using quantitative systems pharmacology (QSP) can be used to guide the design of clinical trials in AD. This study developed a QSP model representing amyloid beta (Aβ) pathophysiology in AD. The model included mechanisms of Aβ monomer production and aggregation to form insoluble fibrils and plaques; the transport of soluble species between the compartments of brain, cerebrospinal fluid (CSF), and plasma; and the pharmacokinetics, transport, and binding of monoclonal antibodies to targets in the three compartments. Ordinary differential equations were used to describe these processes quantitatively. The model components were calibrated to data from the literature and internal studies, including quantitative data supporting the underlying AD biology and clinical data from clinical trials for anti‐Aβ monoclonal antibodies (mAbs) aducanumab, crenezumab, gantenerumab, and solanezumab. The model was developed for an apolipoprotein E ( APOE ) ɛ4 allele carrier and tested for an APOE ɛ4 noncarrier. Results indicate that the model is consistent with data on clinical Aβ accumulation in untreated individuals and those treated with monoclonal antibodies, capturing increases in Aβ load accurately. This model may be used to investigate additional AD mechanisms and their impact on biomarkers, as well as predict Aβ load at different dose levels for mAbs with known targets and binding affinities. This model may facilitate the design of scientifically enriched and efficient clinical trials by enabling a priori prediction of biomarker dynamics in the brain and CSF. … (more)
- Is Part Of:
- CPT: pharmacometrics & systems pharmacology. Volume 12:Number 1(2023)
- Journal:
- CPT: pharmacometrics & systems pharmacology
- Issue:
- Volume 12:Number 1(2023)
- Issue Display:
- Volume 12, Issue 1 (2023)
- Year:
- 2023
- Volume:
- 12
- Issue:
- 1
- Issue Sort Value:
- 2023-0012-0001-0000
- Page Start:
- 62
- Page End:
- 73
- Publication Date:
- 2022-11-06
- Subjects:
- Pharmacokinetics -- Periodicals
Pharmacology -- Periodicals
Pharmacokinetics
Periodicals
615.05 - Journal URLs:
- http://bibpurl.oclc.org/web/52754 ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2163-8306 ↗
http://www.nature.com/psp/index.html ↗
http://www.ncbi.nlm.nih.gov/pmc/journals/2038/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/psp4.12876 ↗
- Languages:
- English
- ISSNs:
- 2163-8306
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25046.xml