George Magrath – Ophthalmology Clinical Trials Predictions for 2023

What’s Happening In Ophthalmology Clinical Trials – Predictions For 2023

Preparedness and adaptability are critical to the success of ophthalmology clinical trials. Our four-part “Predictions For 2023” series aims to give you a glimpse of what will likely happen in the coming year, and how you can be better prepared.

Ophthalmology. By George Magrath, M.D., Chief Executive Officer

Macro perspective

2022 was a period of consolidation. Larger pharmaceutical companies shrank their workforces and focused on developing their primary products, while smaller companies had a more difficult time raising money. Consequently, valuations were lower than in the past. All in all, it became more difficult to focus and execute on capital intensive projects.

Here at Lexitas, we noticed that while the number of new ophthalmic studies remained relatively constant in the past year, the quality of science improved. This means companies really focused on funding the best and most promising science, rather than simply all projects they could.

I think that in the second half of 2023, we’ll probably see more new investments, assuming that the macroeconomic environment is more favorable and interest rates come back down. There will likely be an increase in new funding, which will lead to new projects as well as previously sidelined projects coming back online.

Shift to new ophthalmology indications

In ophthalmology, there has been a general shift to new indications in recent years. This trend will continue in 2023. For the retina, the traditional focus was on diabetic eye disease, wet macular degeneration, and retinal vein occlusion. But now we’re seeing additional indications coming to the forefront. This will include more dry macular degeneration studies, creative ways of addressing inherited retina disease, and a focus on other rare diseases. There is a similar pattern to the anterior segment. Whereas in the past we were focused on general dry eye issues, we now see innovations aimed at less common indications.

Personalized medicines

In recent years, we have seen a greater focus on personalized medicines and this trend will definitely continue. Innovation and scientific progress have allowed us to learn disease pathology at an incredible pace. In the past, diseases of the eye were characterized by the disease phenotype, or the pattern of what the ophthalmologist saw on exam. But today, we can understand the issue on a proteomic and genetic level, and it leads to new types of treatment modalities. Biomarkers such as MMP-9 can be used to identify dry eye diseases caused by inflammation, for example. And the treatment of inflammatory diseases of the posterior segment are continuing to become more targeted. We’ll see more of this type of innovation going forward.

There are also more trials targeting specific patient populations. The goal is to target the right patient with the ‘right’ pathology for the right study. This will give the therapy the best shot at being effective. The caution here is that these types of therapies are extremely complex, often have fewer available patients and tend to be expensive.

Role of ophthalmology datasets and AI

In almost every industry, we’ve seen the increasing use of AI and deep learning to pick up patterns in data that humans can’t see. This is particularly powerful in ophthalmology because there are so many different databases to utilize. One example is the IRIS registry, one of the largest and most robust real-world datasets. I can foresee the development of computer algorithms that can identify patients likely to respond to a particular therapy based on large data sets.

Consolidation of many smaller ophthalmology practices into nationwide practices will lead to additional large datasets. We’ll have the ability to look across the data to understand where patients are located. This type of information is particularly important for site selection as we initiate a new study. Or perhaps we can use real-world databases as a control group vs. patients in a trial.

Another example is the ability to make use of images that are obtained throughout clinical trials. There is a real need in ophthalmology for images to be consolidated in a large, accessible, and structured database. This would help develop new computer learning and computer vision algorithms that can lead to new ophthalmology treatments.  

There are lots of opportunities here and it’s an exciting area ripe for innovation.

Check out Lexitas’ Dr, George Macgrath Goals for 2023 here.