Accelerated research and testing

akbakb Posts: 134 ✭✭✭
If we can digitise and simulate the medical R&D challenge then we would radically accelerate the detection of candidate solutions that are likely to fail in terms of safety or efficacy. This means the traditional phases of a clinical trial could be dedicated to very promising candidates, speeding up the net clinical process.

A giant leap forward would require an accurate digital model of the human cell (including all its types). Easier said than done, but some progress is being made.

Once we have a digital representation then simulated tests can take place extremely quickly to weed out candidates with a low probability of success.

We can go even further, using AI [and later quantum computing] we can rapidly derive new promising candidates. There has been some success in applying AI to this field, and much greater breakthroughs are expected.

Beyond the digitally simulated world, we can use AI and lab robots to grow cultures and mini-organs [perhaps 3D printed] to test the safety and efficacy of candidates. A closely controlled and monitored lab environment might also shed important details on the experiments and allow the AI to learn why candidates fail, and to derive improved solutions.

It's important that this data is shared widely [open data] to accelerate global solutions to many health challenges.

[ PS: For those interested in surgically dealing with brain cancers here are some advanced and innovative microscopy and treatment suggestions: Brain Health Blog. ]
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