Computational models- full Flashcards
(11 cards)
Headings pneumonic
IHGA
Headings (list)
(Introduction)
In vitro vs integrative systems vs computational models
High throughput screens and drug discovery
GWAS
AI / machine learning
(Conclusion)
Introduction subheadings (list)
Mathematics and Bernoulli (1760) seminal thesis
Computational models
Interconnection
(Intro) Mathematics and Bernoulli (1760) seminal thesis
● For some biological processes, the use of an in vitro system is not sufficient.
● Whilst in vitro and in vivo experiments = long been staple of research into biological systems, rapid increase in computational power over the last few decades = enabled emergence of a new experiment field- computational modelling
● Mathematics has been used in biomedical science for centuries
● Bernoulli (1760) seminal thesis- mathematical modelling to demonstrate efficacy of inoculation against smallpox
● Around the same time, Euler applied equations to analyse flow of blood through arteries
● Theoretical models aim to understand biological phenomena
(Intro) Computational models
● Since 60s, the field has grown rapidly, coinciding with an increase in computing power - development of computational models (and in silico experimentation)
● Model/simulation = set of equations/algorithms that aim to represent biological systems. Can vary parameters of the model with computers to study/predict outcomes
● Traditionally BM research has used reductionist approaches
● Helpful to think of a complex system as the sum of its parts. In vitro and in vivo experiments have identified important factors in key processes
(Intro) Interconnection
● But harder to elucidate how cellular events/processes are interconnected, which is ALWAYS the case in biological systems, eg:
● Proteins don’t have one binding partner, form extensive networks; pathways rarely linear, but overlap; rarely is a disease caused by one factor, but interaction of genes/environments
● Computational models can overcome this by taking multiple parameters into account at once. But how well do they replicate real biology?
In vitro vs integrative systems vs computational models subheadings (list)
Cellular changes vs integrative systems
Testing hypotheses
Theobald 2019 (new)
Ethical concerns of in vivo models
(In vitro vs integrative vs computational) Cellular changes vs integrative systems
● For some biological processes, the use of an in vitro system is not sufficient.
● This is particularly true when considering the long-term blood pressure regulation.
● In vitro models may be useful to observe cellular changes, but to observe integrative changes in vivo studies are necessary.
● For example, the control of blood pressure is a feedback process requiring multiple body-systems.
● It is therefore insufficient to examine this integrative process with in vitro models.
● However, in vitro study may be useful for considering the response of very specific cell types.
● Computational models are a cost-effective way of predicting the changes to an integrative system.
● However, these models do have limitations, and cannot be a true replacement for the in vivo studies, which are needed to constantly revise and improve the computational model.
(In vitro vs integrative vs computational) Testing hypotheses
● Computational and microengineered models allow hypotheses to be tested in controlled environments, free from the complex systemic variables that confound in vivo studies (e.g., immune responses, systemic metabolism).
● Theobald et al. (2019) demonstrated this with an organ-on-chip model that mimicked physiological flow and mechanical forces while precisely controlling drug exposure — ideal for testing mechanisms like drug absorption and barrier integrity.
● These models are particularly valuable for studying specific tissue-level responses (e.g., signalling or pharmacodynamics) that would be difficult to isolate in animal or human systems.
● Bridges biological realism with experimental precision.
● However, in vivo studies remain essential to validate findings and ensure that insights gained from these simplified systems hold true in whole-organism physiology.
(In vitro vs integrative vs computational) Theobald 2019 (new)
● Theobald et al in 2019 developed a multi-organ in vitro system for studying the metabolic activation of vitamin D3.
● The authors used microfluidic organ-on-chip platforms in interconnected chambers with HepG2 and RPTEC cells to mimic the liver and kidneys.
● Liquid chromatography with tanden mass spectrometry was used to show the accumulation of 25-hydroxy Vitamin D after the pump driven flow of vitamin D3 through the system.
● Whilst this study used cell lines, and thus suffers from similar disadvantages, it is possible in future that similar work may be possible with organoids, and may be translated to the cardiovascular system.
(In vitro vs integrative vs computational) Ethical concerns of in vivo models
● Animal research in the UK is strictly governed by the Animals (Scientific Procedures)Act 1986, with strict ethical oversight for more humane animal research based on the 3Rs: Replacement, Reduction, and Refinement.
● Replacement encourages alternatives to animal use, such as human cells, computer models, or non-sentient organisms like Drosophila.
● Reduction aims to minimise animal use through techniques like longitudinal imaging, microsampling, and resource sharing.
● Refinement focuses on improving animal welfare by reducing pain and distress, while in vivo human studies face ethical limits and challenges recruiting volunteers for invasive procedures.
