Photo: Ana Isabel Jiménez, Director of Executive Operations and R+D Director at Sylentis. Credit: Sylentis.

By Alba Casilda

In the battle against COVID-19, some companies have put the entirety of their machinery to work. The Director of Executive Operations and R+D at Sylentis, Ana Isabel Jiménez, says “We reacted in record time.” Although this biotech company, belonging to the PharmaMar group, is specialized in ocular, inflammatory, and central nervous system pathologies, in the past months it has also focused on the novel coronavirus.

Thanks to this change, Sylentis has already designed 20 molecules with the potential to create pharmaceuticals specifically for treating COVID-19: “We are in the design phase and validating in vitro.” For Jiménez, “agility” is key to both confronting the pandemic and “differentiating from the competition” and being a truly innovative company.

What steps is Sylentis-PharmaMar taking to incorporate new technologies like artificial intelligence (AI) and data to their innovation processes?

Sylentis was born with a clear focus on being an innovative company. Thanks to interference RNA, we design pharmaceuticals based on oligonucleotides [short sequences of DNA or RNA] to treat illnesses that had not been treatable until this technology was created in 2006. Pharmaceuticals that utilize interference RNA are designed by employing complex algorithms and AI tools. With our SIRFINDER software we are able to design any molecule to address a pathology, whether it be a rare illness or another kind of ailment that has a big impact on society.

What is interference RNA and how does it work?

It is a technology that designs pharmaceuticals differentiated from traditional treatments. Some illnesses occur when proteins are altered, so our products reduce the concentration of those proteins which because they are altered do not work properly and entail the appearance of different pathologies. The information for producing proteins in every organism is in its DNA, which is located in the cell’s nucleus. This is why the DNA information for protein formation is transferred through another molecule, called messenger RNA, which works like a mold producing the proteins.

Molecules designed with interference RNA intervene in the messenger RNA and destroy it. Therefore, if you don’t have a mold to produce the protein, you get rid of the proteins that are not working properly and causing a pathology. In sum, we are not blocking a pathologic protein like traditional pharmaceuticals; we are preventing its production. This process is called genetic silencing. The great advance in this interference RNA technology is designing these specific molecules thanks to biocomputing tools.

Big data, AI, and machine learning: how are these technologies used in interference RNA?

We trace the human genome and design specific molecules for an altered protein through massive data analysis tools. Afterward, our software begins to work with over 30 algorithms, based on big data tools and AI, and it designs a molecule based on parameters including efficiency in silencing the pathologic protein and safety (minimal toxicity), as well as other important parameters to the development of pharmaceuticals like scalability, accounting for genetic variation, and specific silencing that only affects the targeted protein.

Thus, we obtain a series of candidate compounds and we analyze them in in vitro and in vivo studies. Meanwhile, thanks to machine learning techniques, we feed the software information from this analysis so that the machinery learns automatically. This allows us to search for relations that aren’t as evident and design increasingly more efficient molecules. The efficiency of those pharmaceuticals is long-lasting, which is very interesting for chronic illnesses.

One of the challenges that has impeded the fulfillment of the promise of personalized medicine is the enormous research and development cost of pharmaceuticals. Do you see any change with regards to this problem thanks to these technologies?

The time and cost currently involved in researching and development a pharmaceutical are huge. Normally, 4,000 or 5,000 compounds are analyzed to have a positive candidate and begin preclinical trial development. Additionally, it usually takes two to four years to reach the preclinical stage. Interference RNA brings this timeline down to two or three months. However, once we enter clinical trials, these compounds based on interference RNA have to reach regulatory benchmarks just like other types of pharmaceuticals based on other action mechanisms.

Thanks to the agility gained at the beginning, we can develop pharmaceuticals more efficiently, cover unmet needs, and ease the gap with personalized medicine for treating illnesses. COVID-19 is an example of the speed with which we should act in the pharmaceutical sector. Everyone is mobilized.

How has Sylentis-PharmaMar responded to this pandemic?

The first thing that Pharma-Mar did was reposition pharmaceuticals that were already on the market and use them for COVID-19. We are working with Aplidin, an antitumor pharmaceutical that treats hematologic cancer and that after positive results in in vitro and in vivo tests, began a clinical trial. At the same time, Genómica, another company in the group, was the first company in developing diagnostic kits, together with the Carlos III Hospital in Madrid, and achieve CE certification marking.

For our part, at Sylentis we are using our tools to design pharmaceuticals specific to COVID-19 with two different focuses. The first consists of attacking the virus’ replication by silencing the virus’ proteins. The second is based on developing interferences RNA directed at the host cell in the respiratory tract, to prevent the entry of the virus in human cells, thus either blocking its propagation or silencing proteins that the virus needs for its replication inside the infected cell.

“We are using all of our tools to develop pharmaceuticals specific to COVID-19.”

For all of this, we are working with groups specialized in formulations with the goal of designing therapeutic missiles to lead pharmaceuticals directly to the target tissue, in this case pulmonary tissue.

Collaboration is currently a trend in business. What is your position on the dichotomy between competition and collaboration?

The pharmaceutical sector tends to be very individualistic due to intellectual property concerns. Nonetheless, at Sylentis we have established collaborations in which we regulate this issue. For example, we were able to develop a pharmaceutical to treat dry eye thanks to a collaboration agreement with a Spanish university. In general, the extent of our collaboration with public institutions is wide because we need experts in the target treatments we tackle.

What new capabilities do corporate leaders need to take on this new way of working?

You have to understand an innovative culture that goes bottom–up. It’s important to have a CEO that understands innovation, since innovation often does not lead to positive results in the short or even medium terms.

A CEO should not just be a good economic manager. Some economists say that R+D is a waste; I say it is an investment. They must also foster creativity, participation, and the spread of ideas. You need teams that think outside the box and maintain the company’s culture. That said, innovations must be in sync with the organization’s objectives in order to all work in the same direction.

“Some economists say that R+D is a waste; I say it is an investment.”

What challenges does the pharmaceutical sector face in knowing how to act in this new context?

Companies need to change their mentality, integrate technologies from different sectors, and make use of all existing knowledge. In Spain and Europe there is a very high quality of scientific research, but there is a gap between what is developed at universities and what is later offered on the market. Spain is cutting-edge in scientific excellence and the number of publications, but many products don’t become reality.

“In Spain and Europe there is a gap between what is developed at universities and what is offered on the market.”

We have to adapt to new sectors and create multidisciplinary teams. We have to make an effort to integrate two worlds: science and computing. Likewise, we have to see that it isn’t bad to lean on different entities to develop pharmaceuticals. We have to be clear that it is better to share intellectual property and collaborate to create pharmaceuticals, even if it entails future profit sharing.

This will be beneficial for the development and subsequent commercialization of a potential pharmaceutical and thus ensure patients access new treatments combining efforts and sharing knowledge. This will lead us to generate new commercial relationships where we all win and establish new business models where intellectual property is shared along with possible economic benefits derived from the commercialization of the product.

Published by OPINNO © 2022 MIT TECHNOLOGY REVIEW spanish edition