Lab Experiments Lead Scientists Astray
Lab cancer tumours are not like those of patients, so scientists’ results are often misleading.
Scientists test thousands of potential drugs in the lab. Of those, only a few pass through the eye of the needle to be tested on humans. But the selection process is not optimal. Drugs that should never have been tested on humans pass, whereas treatments that could have saved lives, do not.
The problem is that scientists make their cancer cell experiments in culture dishes or animal tumours – and those do not resemble what is going on in patients. A culture dish is nothing like the environment of different cell types, blood vessels, and chemical substances inside a body. Moreover, differences between animals and people concerning metabolism, immune system, tissue structure, etc., mean that animal tumours develop differently from those of humans.
So, the drugs have very different conditions in labs and patients, and the chance that the effect of an animal experiment will be the same in humans is small.
Today, scientists know that this type of animal experiments are very poor at predicting the effect of a treatment on humans. Lung cancer cells growing in the thigh will not cause anything like lung cancer. And scientists also get the wrong impression of the treatment’s effect, if they test it on new, small tumours – human patients are typically diagnosed with cancer, when their tumours have grown rather large.
The scientists’ choice of patients for the SPI77 experiment was probably not optimal either. Like other liposomes, it is difficult for SPI 77 to get access to cancer cells, if the tumour's blood vessels are not sick and leaky. Many tumours have healthy blood vessels without holes, and patients with such tumours will typically not benefit much from liposome treatment. If scientists had actively selected patients with leaky tumour blood vessels, SPI-77 might have had a better chance of killing the cancer.
Since then, scientists have become better at creating lab tumours similar to those of patients. They have also developed new methods, which can more accurately predict which patients will react the best to a specific treatment. The improvements mean that scientists are better at estimating which drugs have a real effect on humans and selecting the cancer patients who will benefit the most from the treatment.
Moreover, scientists have invented groundbreaking new treatments that were completely unimaginable a few decades ago.
Artificial intelligence boost
In 2017, the US authorities swiftly approved a new treatment known as Kymriah, which had eliminated any trace of cancer in 83 % of the patients it had been tested on; patients, who had fruitlessly tried more traditional treatments.
Kymriah consists of the patients’ own immune cells, which are extracted from the his blood, after which a new gene is inserted that enables them to recognize cancer cells. When the immune cells are injected back into the patient, they find the tumour and attack it. The treatment is extremely efficient, and media throughout the world praised it as something close to a medical miracle. Is Kymriah the ultimate cure that scientists have been looking for for so long?
Not quite. Kymriah could activate the patient’s immune system so efficiently that it also attacks the healthy cells of the body. When a similar treatment was tested in 2016, it killed five patients. The fatal side effects mean that doctors only use Kymriah as the last resort, when other, less hazardous treatments have failed.
However, Kymriah is not necessarily a dead end, and the same goes for liposomes. Every day, scientists learn more about the treatments’ weaknesses and the biology of cancer, and they use the knowledge to optimise existing therapies and develop new ones. Moreover, revolutionizing technology ensures that scientists can soon make progress much faster than they used to. One technology comes from the US company twoXAR, which equips computers with artificial intelligence that is able to spot new medication against cancer, etc. The system can very quickly go through huge quantities of data from labs and hospitals throughout the world, delving into cancer cell genes, taking a close look at the chemical make-up of existing drugs and going over previous experiments on animals and humans. After the extensive analysis, the system identifies unknown weaknesses in the cancer cells and suggests drugs that take advantage of them; a process that would have taken years to carry out for scientists. The result is that doctors can soon get access to a large arsenal of efficient weapons against cancer.