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Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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In Silico Clinical Trials for Cardiovascular Disease
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In Silico Clinical Trials: Is It Possible?

Simon Arsène1, Yves Parès1, Eliott Tixier1

  • 1Novadiscovery SA, Lyon, France.

Methods in Molecular Biology (Clifton, N.J.)
|September 13, 2023
PubMed
Summary
This summary is machine-generated.

In silico trials, a key part of model-informed drug development (MIDD), accelerate drug discovery. This work proposes integrated workflows and tools to overcome adoption barriers for more efficient clinical research.

Keywords:
Clinical trialsDigital twinsDrug developmentDrug regulationHealth technology assessmentIn silico trialsKnowledgeModeling and simulation (M&S)Software platformSynthetic control armsSystems biologySystems pharmacology

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Area of Science:

  • Computational biology and pharmacology
  • Drug development and regulatory science

Background:

  • Modeling and simulation (M&S), including in silico trials, are crucial for accelerating drug development and reducing costs within model-informed drug development (MIDD).
  • Diverse M&S approaches, from data-driven to physiologically-based models, present challenges in integration due to differing setups and data requirements.
  • Regulatory bodies and developers are increasingly exploring in silico trials to refine, reduce, or replace traditional clinical trials.

Purpose of the Study:

  • To address challenges in widespread in silico trial adoption by proposing integrated workflows and collaborative tools.
  • To provide a coherent set of solutions for establishing best-practice workflows in in silico clinical trial development.
  • To outline the characteristics of an in silico trial software platform using jinkō.ai as an example.

Main Methods:

  • Development of a dedicated workflow for the in silico clinical trial lifecycle, incorporating principles from systems biology and quantitative systems pharmacology.
  • Integration of specific steps for regulatory qualification within the proposed workflow.
  • Description of key features for an in silico trial software platform implementation.

Main Results:

  • A structured workflow for in silico clinical trial development and regulatory qualification is presented.
  • The jinkō.ai platform is highlighted as an example of an end-to-end in silico clinical trial solution.
  • The breakdown of silos between distinct modeling approaches is observed.

Conclusions:

  • Integrated workflows and collaborative tools are essential for overcoming barriers to in silico trial adoption.
  • In silico trials hold significant promise for refining, reducing, and potentially replacing clinical research, ushering in a new era of efficient drug development.
  • Future applications include synthetic control strategies and digital twins, further enhancing drug development efficiency.