Quantitative Systems Pharmacology Models: Potential Tools for Advancing Drug Development for Rare Diseases

被引:1
|
作者
Neves-Zaph, Susana [1 ]
Kaddi, Chanchala [1 ]
机构
[1] Sanofi US, Translat Dis Modeling Translat Med & Early Dev, Bridgewater, NJ 08807 USA
关键词
BLOOD-COAGULATION NETWORK; HEMOPHILIA-B; FITUSIRAN PROPHYLAXIS; GENE-THERAPY; OPEN-LABEL; MULTICENTER; DISCOVERY; DIAGNOSIS; PREDICT; PEOPLE;
D O I
10.1002/cpt.3451
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Rare diseases, affecting millions globally, present significant drug development challenges. This is due to the limited patient populations and the unique pathophysiology of these diseases, which can make traditional clinical trial designs unfeasible. Quantitative Systems Pharmacology (QSP) models offer a promising approach to expedite drug development, particularly in rare diseases. QSP models provide a mechanistic representation of the disease and drug response in virtual patients that can complement routinely applied empirical modeling and simulation approaches. QSP models can generate digital twins of actual patients and mechanistically simulate the disease progression of rare diseases, accounting for phenotypic heterogeneity. QSP models can also support drug development in various drug modalities, such as gene therapy. Impactful QSP models case studies are presented here to illustrate their value in supporting various aspects of drug development in rare indications. As these QSP model applications continue to mature, there is a growing possibility that they could be more widely integrated into routine drug development steps. This integration could provide a robust framework for addressing some of the inherent challenges in rare disease drug development.
引用
收藏
页码:1442 / 1451
页数:10
相关论文
共 50 条
  • [21] Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases
    Giulio Napolitano
    Canan Has
    Anne Schwerk
    Jui-Hung Yuan
    Carsten Ullrich
    Pharmaceutical Medicine, 2024, 38 : 79 - 86
  • [22] Innovative approaches in CNS clinical drug development: Quantitative systems pharmacology
    Lacroix, Clemence
    Soeiro, Thomas
    Le Marois, Marguerite
    Guilhaumou, Romain
    Casse-Perrot, Catherine
    Jouve, Elisabeth
    Rohl, Claas
    Belzeaux, Raoul
    Micallef, Joelle
    Blin, Olivier
    THERAPIE, 2021, 76 (02): : 111 - 119
  • [23] A framework for simplification of quantitative systems pharmacology models in clinical pharmacology
    Derbalah, Abdallah
    Al-Sallami, Hesham
    Hasegawa, Chihiro
    Gulati, Abhishek
    Duffull, Stephen B.
    BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 2022, 88 (04) : 1430 - 1440
  • [24] A Quantitative Systems Pharmacology Model of Colonic Motility to Aid Drug Discovery and Development
    Zhang Liming
    Raibatak, Das
    Lucia, Wille
    Chen Chunlin
    Jangir, Selimkhanov
    Jill, Wykosky
    Wendy, Winchester
    Cristina, Almansa
    John, Burke
    Fei, Hua
    Majid, Vakilynejad
    JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS, 2018, 45 : S71 - S71
  • [25] Integration not isolation: arguing the case for quantitative and systems pharmacology in drug discovery and development
    Agoram, Balaji M.
    Demin, Oleg
    DRUG DISCOVERY TODAY, 2011, 16 (23-24) : 1031 - 1036
  • [26] Applying quantitative and systems pharmacology to drug development and beyond: An introduction to clinical pharmacologists
    Ramasubbu, Mathan Kumar
    Paleja, Bhairav
    Srinivasann, Anand
    Maiti, Rituparna
    Kumar, Rukmini
    INDIAN JOURNAL OF PHARMACOLOGY, 2024, 56 (04) : 268 - 276
  • [27] Deep learning tools for advancing drug discovery and development
    Sagorika Nag
    Anurag T. K. Baidya
    Abhimanyu Mandal
    Alen T. Mathew
    Bhanuranjan Das
    Bharti Devi
    Rajnish Kumar
    3 Biotech, 2022, 12
  • [28] Deep learning tools for advancing drug discovery and development
    Nag, Sagorika
    Baidya, Anurag T. K.
    Mandal, Abhimanyu
    Mathew, Alen T.
    Das, Bhanuranjan
    Devi, Bharti
    Kumar, Rajnish
    3 BIOTECH, 2022, 12 (05)
  • [29] USING QUANTITATIVE SYSTEMS PHARMACOLOGY (QSP) MODELS TO CHARACTERIZE THE PK OF NOVEL DRUG MODALITIES
    Nobisch, Jamie
    DRUG METABOLISM AND PHARMACOKINETICS, 2024, 55
  • [30] Quantitative Systems Pharmacology: A Case for Disease Models
    Musante, C. J.
    Ramanujan, S.
    Schmidt, B. J.
    Ghobrial, O. G.
    Lu, J.
    Heatherington, A. C.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2017, 101 (01) : 24 - 27