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Accurately simulating biological systems in the cloud to run a virtual clinical trial is like trying to predict the exact weather for Washington DC at a specifi

Accurately simulating biological systems in the cloud to run a virtual clinical trial is like trying to predict the exact weather for Washington DC at a specific date and time hundreds of years from now using weather forecast models. It’s pretty much impossible with current biomedical knowledge. To simulate humans well enough to eliminate a clinical trial, you would have to simulate every single cell, organ, and organ system as well as the substantial population of bacterial and fungal microorganisms that live on and inside humans (as well as all their unique biology too). Building such a simulation would require a level of knowledge of biology that the human race currently does not possess.

dflock 8y ago
Also, computronium.
snaky 8y ago
That is and will stay impossible no matter how many resources for simulation you have, actually. > This technique, when applied to the real world, is sometimes useful, but can sometimes also lead to self-deception. This technique is called modelling. When constructing a model, the following idealization is made: certain facts which are only known with a certain degree of probability or with a certain degree of accuracy, are considered to be “absolutely” correct and are accepted as “axioms”. The sense of this “absoluteness” lies precisely in the fact that we allow ourselves to operate with these “facts” according to the rules of formal logic, in the process declaring as “theorems” all that we can derive from them. > It is obvious that in any real-life activity it is impossible to place total reliance on such deductions, if only because the parameters of the phenomena studied are never known absolutely exactly and a small change in parameters (for example, in the initial conditions of a process) can totally change the result. It is for this reason that a reliable long-term weather forecast is impossible and will remain impossible, no matter how much we develop computers and devices which record initial conditions. https://dsweb.siam.org/The-Magazine/All-Issues/vi-arnold-on-teaching-mathematics https://dsweb.siam.org/The-Magazine/All-Issues/vi-arnold-on-...

dflock 8y ago

Also, computronium.

snaky 8y ago

That is and will stay impossible no matter how many resources for simulation you have, actually. > This technique, when applied to the real world, is sometimes useful, but can sometimes also lead to self-deception. This technique is called modelling. When constructing a model, the following idealization is made: certain facts which are only known with a certain degree of probability or with a certain degree of accuracy, are considered to be “absolutely” correct and are accepted as “axioms”. The sense of this “absoluteness” lies precisely in the fact that we allow ourselves to operate with these “facts” according to the rules of formal logic, in the process declaring as “theorems” all that we can derive from them. > It is obvious that in any real-life activity it is impossible to place total reliance on such deductions, if only because the parameters of the phenomena studied are never known absolutely exactly and a small change in parameters (for example, in the initial conditions of a process) can totally change the result. It is for this reason that a reliable long-term weather forecast is impossible and will remain impossible, no matter how much we develop computers and devices which record initial conditions. https://dsweb.siam.org/The-Magazine/All-Issues/vi-arnold-on-teaching-mathematics https://dsweb.siam.org/The-Magazine/All-Issues/vi-arnold-on-...