One of the basic activities of the pharmaceutical industry is undoubtedly that of knowing and creating small and large molecules. The aims are manifold, the most obvious of all, the development of new drugs. But all the molecules studied are nothing more than systems based on quantum physics. This is the first reason that brings the interest of the sector to the QC at the highest level.
But that of molecular formation is only one of the fields of application. As happens and has already happened with artificial intelligence, there will be a use of quantum computing also in experimentation, security, and controls, as well as in the archiving not only of molecules but also of more complex systems. All these complex processes can be made very fast and with less and less room for error. Pharmaceutical companies have always surrounded themselves with digital tools such as molecular dynamics simulations (MD) and ultimately artificial intelligence (AI). The next phase will certainly be quantum computing (QC). Just as it was done long ago with artificial intelligence, a technological transition is expected. An initial synergistic collaboration of AI and QC that will lead to incredible developments.
The “status quo”
Currently, molecules are created with a methodology called “computer-assisted drug discovery” (CADD). The computers used are the classic ones that take a lot of time, work, and money to perform basic calculations and screening of medium-small molecules. The same CADD system on quantum computers could drastically reduce the entire supply chain. This means that those who work in the sector with CADD will not have to upset the working methods that are already based on chemistry and quantum but will be able to do it more efficiently.
Quality control would not be limited only to assisting the discovery of drugs. This will always remain the field of action and the ultimate goal of all the research and development sectors of the pharmaceutical industry. But it can give an exponential acceleration to data management or in silico experiments for example. These are nothing more than clinical studies carried out starting from completely simulated elements.
They have the function of saving time and money, in anticipation and instead of the live rehearsals, that they would be preparatory to. Silico tests require an enormous amount of work and therefore enormous computing power to process all the simulation models. Just think of the enormous variety of participants and the amount of data. The QC will be an absolutely efficient ally, in terms of costs, time and money. Certainly thanks to the possibility of simulating even large molecules and their reactivity in a very efficient way.
Given the enormous potential of quality control, many high-profile startups together with large multinationals in the sector are proposing to create partnerships with pharmaceutical companies. Quantum players and the pharmaceutical industry will be increasingly interested in each other. Reason is easy to understand: investments in the QC sector is projected to be in the billions of dollars by 2030.
The key tools
Quality control will help predict molecular properties with tremendous accuracy. Qc can allow researchers to examine computational libraries against multiple possible structures at the same time. In the long run, quality control can improve simulation processes using machine learning (ML) algorithms to discover new structure-property relationships. Once a sufficient degree of autonomy is achieved, QC may be able to generate new sets of drug libraries that are no longer limited to small molecules. This could lead to automated drug discovery as well. How? Thanks to a huge structural library of biologically relevant targets. This would be screened against drug-like molecules using high-throughput approaches. Also using ML algorithms, QC could be used to “deepfake” missing data points throughout the search process, generating a false data type. This could be particularly useful in all pharmaceutical sectors where there is a paucity of experimental data.
Not just drug development
The QC will provide significant support in stepping up the activity related to clinical trials. Just think of all the patient cataloging processes or the causality analyses related to the onset of side effects. Therefore, not only research and development but also safety and experimentation, active and planned. The same safety will also be guaranteed in the optimization of toxicity forecasts or in the processing of doses for example.
Quality control in the pharmaceutical sector will initiate a virtuous circle that will lead, among other things, to optimizing processes related to logistics such as procurement management. The support to the commercial sector will be significant, also facilitating the sales sector.
In order for this to happen, however, it will be necessary that the staff of the pharmaceutical industry also vary and that the sectors no longer find barriers. Research and development, as well as logistics and the sales sector, will have to be synergistically connected, but this will only be possible if the pharmaceutical sector increasingly integrates the QC methodology. Considering the volume of business, the choice seems obvious and there are already many companies in the sector looking for people skilled in quantum computing and digital technologies.