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Multiscale Modeling in the Clinic: Drug Design and Development

  • Multi-Scale Modeling in the Clinic
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Abstract

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (1) excitable systems and applications in cardiac disease; (2) stem cell driven complex biosystems; (3) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (4) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (5) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models.

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Abbreviations

ABM:

Agent-based model

AMD:

AMD3100

BMSC:

Bone marrow stromal cell

BSV:

Between-subject variability

BZM:

Bortezomib

CAD:

Computer-aided design

CG:

Coarse-grained

CXCR4:

C-X-C chemokine receptor type 4

DPD:

Dissipative particle dynamics

ECM:

Extracellular matrix

EPR:

Enhanced permeability and retention

HPV:

Human papillomavirus

IFP:

Interstitial fluid pressure

MC:

Monte Carlo

MCMC:

Markov chain Monte Carlo

MD:

Molecular dynamics

MF:

Multiscale factorization

MIC:

Myeloma initiating cell

MM:

Multiple myeloma

NC:

Nanocarrier

NP:

Nanoparticle

NS:

Navier–Stokes

PBPK:

Physiologically-based pharmacokinetic

PC:

Cancer progenitor cell

PDB:

Protein Data Bank

QM/MM:

Quantum mechanics/molecular mechanics

RUV:

Residual unknown variability

SCB:

Systems chemical biology

SDF1:

Stromal cell-derived factor 1

TMM:

Terminal multiple myeloma cell

WHAM:

Weighted histogram analysis method

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Acknowledgments

This work was supported in part by NIH grants R01CA138264 (ASP), U01HL126273 (CEC), U01EB016027 (DME), R01EB006818 (DME), R01-GM-115839 and P30-DK-42086 (GA), R01GM077138 (JPS) and R15EB015105 (YL) as well as EPA grant R835001 (JPS). WRC was funded under the Laboratory Directed Research Program at the Pacific Northwest National Laboratory. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC06-76RLO.

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Authors and Affiliations

  1. Department of Pharmacology, University of California, Davis, CA, USA

    Colleen E. Clancy

  2. Department of Surgery, University of Chicago, Chicago, IL, USA

    Gary An

  3. Computational Biology Group, Pacific Northwest National Laboratory, Richland, WA, USA

    William R. Cannon

  4. Department of Mechanical Engineering and Mechanics, Bioengineering Program, Lehigh University, Bethlehem, PA, USA

    Yaling Liu

  5. Department of Biomedical Engineering, University of Houston, Houston, TX, USA

    Elebeoba E. May

  6. Department of Chemistry, Indiana University, Bloomington, IN, USA

    Peter Ortoleva

  7. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

    Aleksander S. Popel

  8. Biocomplexity Institute, Indiana University, Bloomington, IN, USA

    James P. Sluka

  9. Department of Radiology, Wake Forest University, Winston-Salem, NC, USA

    Jing Su & Xiaobo Zhou

  10. Clinical Pharmacology and DMPK, MedImmune, Cambridge, UK

    Paolo Vicini

  11. Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA

    David M. Eckmann

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Correspondence to Colleen E. Clancy or David M. Eckmann.

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Associate Editor Thomas Yankeelov oversaw the review of this article.

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Clancy, C.E., An, G., Cannon, W.R. et al. Multiscale Modeling in the Clinic: Drug Design and Development. Ann Biomed Eng 44, 2591–2610 (2016). https://doi.org/10.1007/s10439-016-1563-0

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