The strategy of designing innovative drug with the use of AI/MM

Artificial intelligence (AI) and molecular modeling (MM) are now being increasingly used to design innovative drugs. These state-of-the art technologies allow for faster and more precise development of new pharmacological substances, which can speed up the drug development process and reduce costs related to clinical trials.

AI can be used to analyze vast amounts of biological, chemical, and biochemical data, which helps identify potential therapeutic targets and design chemical compounds with desired therapeutic properties. Molecular modeling (also called biological modeling) aims at simulating interactions between the drug and the body, which makes it possible to predict the efficacy and safety of a potential drug.

By combining these two technologies, more effective and safe medicines tailored to individual patients’ needs can be created. Also, drug design using AI and molecular modeling can speed up the process of researching new therapies, which can be beneficial for both patients and pharmaceutical companies.

Drug development process

The designing of potential drugs is a multi-stage undertaking involving the results of the work conducted by R&D departments, molecular modeling, as well as pre-clinical and clinical trials. This process of potential drug development can be presented as follows:

• A goal, which is a technical goal, is identified, namely, a target of a potential drug in the body that may be involved in the disease/preventive process is defined and such a target may be a protein, enzyme or other molecule playing a significant role;
• Potential drug candidates are developed, i.e. chemical structures that can interact with the target and lead to the modulation of its activity, using the analysis and screening of extensive resources of chemical compound libraries and biological modeling to predict whether and how identified molecules will interact with the target,
• Process optimization is carried out, which involves the optimization of the properties of a promising drug candidate to improve its effectiveness, safety, pharmacokinetics, etc.,
• A selected potential drug is studied in pre-clinical trials, which means that before a new drug can be tested in humans, it must undergo rigorous tests to assess its safety, therapeutic effectiveness, potential side effects, and such pre-clinical trials may include testing the drug in cell cultures, animal models, and other experimental systems;
• After all the aforementioned stages have been completed, it is time for so-called clinical trials, in which the drug candidate also undergoes rigorous tests in humans, involving volunteers, to assess its safety and effectiveness;
• The final stage is regulatory approval – when the investigated drug has successfully passed all the trial stages and has a favorable risk-benefit profile, a set of relevant documents is filed with regulatory agencies, such as the FDA, for approval, so that the drug could be placed on the market and sold to patients.

As you can see, designing innovative drug candidates requires a combination of scientific knowledge, experimental research, technological tools as well as regulatory and legal knowledge to provide new treatments to patients in need of them. The use of AI and molecular modeling in drug design has the potential to revolutionize the pharmaceutical industry by accelerating the development of modern drug structures. By combining AI algorithms with advanced biological models, it is possible to effectively identify potential drug candidates, predict their effectiveness and safety, and optimize their properties for specific therapeutic applications.

Powerful tools to design innovations

A unique advantage of using AI in drug design is its ability to analyze very large amounts of data from a variety of sources, such as genetic information, protein structures, chemical properties of diverse structures to identify patterns and relations that may not be visible at first glance. AI can also be used to predict the pharmacokinetics and pharmacodynamics of potential drug candidates, thus enabling the optimization of their properties to obtain maximum effectiveness and minimize side effects.

Molecular modeling is another powerful tool that can be applied along with AI to design potential innovative drugs. Behavioral simulations of biological systems at the molecular level can guide scientists as regards interactions of drugs with their targets and predict their impact on individual, selected cellular pathways. All the information obtained as a result of AI and MM-powered research and development can be used to design new drug candidates and optimize their properties for new medical applications.

Possible impact on the company’s strategy

To sum up, a comprehensive technical tool of the 21st century combining artificial intelligence and molecular modeling holds great promise for accelerating the development of drug candidates and, consequently, of innovative ways to administer therapeutic treatments against a wide spectrum of existing diseases. By exploiting a great potential of these technologies, Innovators can design innovative drugs with increased efficacy, safety and selectivity, which will ultimately benefit patients and lead to advancements in the field of medicine.

Of course, in the context of the above, the question arises how modern drugs will affect the company’s strategies and the protection of intellectual property created in the course of R&D work. The above-mentioned American Food and Drug Administration, which is a government institution dealing with, among other things, drug control and registration, approved many modern drugs in 2024, for example:

• On 22 November 2024, Rapiblyk (with the active substance of landiolol) was approved for use in the treatment of tachycardia;
• On 15 November 2024, Revuforj (with the active substance of revumenib) was approved for use in the treatment of relapsed or refractory acute leukemia;
• On 10 October 2024, Itovebi (with the active substance of inavolisib) was approved for use in the treatment of locally advanced or metastatic breast cancer.

The European Medicines Agency (EMEA) is also worth mentioning, as it deals with the supervision and registration of drugs, and, like the FDA, the EMEA approved many innovative drugs in 2024, for example:

• On 14 November 2024, Elahere (with the active substance of mirvetuximab soravtansine) was approved for use in the treatment of ovarian, fallopian tube and peritoneal cancers;
• On 13 November 2024, Opuviz (with the active substance of aflibercept) was approved

for use in the treatment of macular degeneration, macular edema, diabetic complication, retinal vein occlusion.

As indicated above, many modern drugs are registered by pharmaceutical companies for a variety of therapies in humans. However, from a strategic and business point of view, IP protection would seem crucial. Of course, many IP-related questions arise, namely:

1. Do pharmaceutical companies focus on obtaining patent rights to inventions?
2. Are pharmaceutical companies interested in obtaining as many patents as possible and in what possible available time they would like to obtain the patent right?
3. How long would such companies wish to maintain the patent right in force?
4. Which territories of protection are most desirable for pharmaceutical companies?

The above questions are probably the ones that pharmaceutical companies ask themselves. An interesting aspect is a growing trend in the pharmaceutical sector regarding an increase in the number of patent rights to modern, commercially marketed drugs for use in the treatment of humans. Therefore, to all the questions presented in this article and any other questions asked by those interested in the activities of the pharmaceutical sector, answers are either already available or will be available soon, while others will remain a secret constituting the know-how of individual enterprises.