New study demonstrates the potential for machine learning to accelerate the development of innovative drug delivery technologies.
Scientists at the University of Toronto have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine learning algorithms to accelerate drug formulation could reduce the time and cost associated with drug development, making promising new medicines available faster.
The study will be published today (January 10, 2023) in the journal Nature Communications and is one of the first to apply machine learning techniques to the design of polymeric long-acting injectable drug formulations.
“This study takes a critical step towards data-driven drug formulation development with an emphasis on long-acting injectables,” said Christine Allen, professor in pharmaceutical sciences at the Leslie Dan Faculty of Pharmacy, University of Toronto. “We’ve seen how machine learning has enabled incredible leap-step advances in the discovery of new molecules that have the potential to become medicines. We are now working to apply the same techniques to help us design better drug formulations and, ultimately, better medicines.”
Considered one of the most promising therapeutic strategies for the treatment of chronic diseases, long-acting injectables (LAI) are a class of advanced drug delivery systems that are designed to release their cargo over extended periods of time to achieve a prolonged therapeutic effect. This approach can help patients better adhere to their medication regimen, reduce side effects, and increase efficacy when injected close to the site of action in the body. However, achieving the optimal amount of drug release over the desired period of time requires the development and characterization of a wide array of formulation candidates through extensive and time-consuming experiments. This trial-and-error approach has created a significant bottleneck in LAI development compared to more conventional types of drug formulation.
“AI is transforming the way we do science. It helps accelerate discovery and optimization. This is a perfect example of a ‘Before AI’ and an ‘After AI’ moment and shows how drug delivery can be impacted by this multidisciplinary research,” said Alán Aspuru-Guzik, professor in chemistry and computer science, University of Toronto who also holds the CIFAR Artificial Intelligence Research Chair at the Vector Institute in Toronto.
To investigate whether machine learning tools could accurately predict the rate of drug release, the research team trained and evaluated a series of eleven different models, including multiple linear regression (MLR), random forest (RF), light gradient boosting machine (lightGBM), and neural networks (NN). The data set used to train the selected panel of machine learning models was constructed from previously published studies by the authors and other research groups.
“Once we had the data set, we split it into two subsets: one used for training the models and one for testing. We then asked the models to predict the results of the test set and directly compared with previous experimental data. We found that the tree-based models, and specifically lightGBM, delivered the most accurate predictions,” said Pauric Bannigan, research associate with the Allen research group at the Leslie Dan Faculty of Pharmacy, University of Toronto.
As a next step, the team worked to apply these predictions and illustrate how machine learning models might be used to inform the design of new LAIs, the team used advanced analytical techniques to extract design criteria from the lightGBM model. This allowed the design of a new LAI formulation for a drug currently used to treat ovarian cancer. “Once you have a trained model, you can then work to interpret what the machine has learned and use that to develop design criteria for new systems,” said Bannigan. Once prepared, the drug release rate was tested and further validated the predictions made by the lightGBM model. “Sure enough, the formulation had the slow-release rate that we were looking for. This was significant because in the past it might have taken us several iterations to get to a release profile that looked like this, with machine learning we got there in one,” he said.
The results of the current study are encouraging and signal the potential for machine learning to reduce reliance on trial-and-error testing slowing the pace of development for long-acting injectables. However, the study’s authors identify that the lack of available open-source data sets in pharmaceutical sciences represents a significant challenge to future progress. “When we began this project, we were surprised by the lack of data reported across numerous studies using polymeric microparticles,” said Allen. “This meant the studies and the work that went into them couldn’t be leveraged to develop the machine learning models we need to propel advances in this space,” said Allen. “There is a real need to create robust databases in pharmaceutical sciences that are open access and available for all so that we can work together to advance the field,” she said.
To promote the move toward the accessible databases needed to support the integration of machine learning into pharmaceutical sciences more broadly, Allen and the research team have made their datasets and code available on the open-source platform Zenodo.
“For this study our goal was to lower the barrier of entry to applying machine learning in pharmaceutical sciences,” said Bannigan. “We’ve made our data sets fully available so others can hopefully build on this work. We want this to be the start of something and not the end of the story for machine learning in drug formulation.”
Cancer and AI – Can ChatGPT Be Trusted?
A study published in the Journal of The National Cancer Institute Cancer Spectrum delved into the increasing use of chatbots and artificial intelligence (AI) in providing cancer-related information. The researchers discovered that these digital resources accurately [...]
Breathing New Life: Oxygen Therapy Improves Heart Function in Long COVID Patients
A small trial has found that hyperbaric oxygen therapy (HBOT) may help restore proper heart function in patients with post-COVID syndrome, with participants in the HBOT group experiencing a significant increase in global longitudinal [...]
Wireless Brain-Spine Interface: A Leap Towards Reversing Paralysis
Summary: In a pioneering study, researchers designed a wireless brain-spine interface enabling a paralyzed man to walk naturally again. The ‘digital bridge’ comprises two electronic implants — one on the brain and another on the [...]
New study reveals a gel that promises to wipe out brain cancer for good
An anti-cancer gel promises to wipe out glioblastoma permanently, a feat that's never been accomplished by any drug or surgery. So what makes this gel so special? Scientists at Johns Hopkins University (JHU) have [...]
New production process for therapeutic nanovesicles
Particles known as extracellular vesicles play a vital role in communication between cells and in many cell functions. Released by cells into their environment, these “membrane particles” consist of a cellular membrane carrying a [...]
Could studying African killifish be the secret cure to sarcopenia?
The Australian Regenerative Medicine Institute (ARMI) at Monash University suggests that muscle wasting, known as sarcopenia, may be reversed in late-life The study utilized the African killifish as a model and found that muscles revert [...]
Virtual AI Radiologist: ChatGPT Passes Radiology Board Exam
The most recent version of ChatGPT, an AI chatbot developed for language interpretation and response generation, has successfully passed a radiology board-style exam, demonstrating both its potential and limitations, according to research studies published [...]
Harnessing Energy Waves: Smart Material Prototype Challenges Newton’s Laws of Motion
University of Missouri researchers designed a prototype of a small, lightweight active ‘metamaterial’ that can control the direction and intensity of energy waves. Professor Guoliang Huang of the University of Missouri has developed a [...]
Nanotechnology revolutionizes the way cancer-fighting T cells navigate and combat tumors
Vanderbilt researchers are bolstering the fight against cancer with technology that enhances the effectiveness of T cells that attack tumors. The cutting-edge research was recently published in the journal Science Immunology. Cancers co-opt both [...]
Molecular “Superpower” of Antibiotic-Resistant Bacteria Revealed in New Research
A species of ordinary gut bacteria that we all carry flourishes when the intestinal flora is knocked out by a course of antibiotics. Since the bacteria is naturally resistant to many antibiotics, it causes problems, particularly [...]
Human DNA Is All Over The Planet, And Scientists Are Worried
Every skin flake, hair follicle, eyelash, and spit drop cast from your body contains instructions written in a chemical code, one that is unique to you. According to a new study, technology has advanced [...]
Long COVID: The Invisible Consequence of Socioeconomic Inequality
A recent study conducted by the Universities of Southampton and Oxford reveals a strong correlation between the incidence of long COVID and the level of area-specific deprivation. It found that individuals from the most deprived regions are 46 [...]
Mutation Mystery: Unraveling the Secret Behind COVID-19’s Rapid Spread
Molecular modeling suggests structural consequences of an early protein mutation that promoted viral transmission. RIKEN researchers discovered that an early mutation (D614G) in the SARS-CoV-2 virus may have contributed to its rapid spread by altering the spike [...]
Protein nanoparticle vaccine with adjuvant improves immune response against influenza
A novel type of protein nanoparticle vaccine formulation containing influenza proteins and adjuvant to boost immune responses has provided complete protection against influenza viral challenges, according to a new study published by researchers in [...]
Decoding Long COVID: NIH Study Exposes the Inner Workings of Neurological Symptoms
A NIH study on twelve Long COVID patients found differences in immune cell profiles and autonomic dysfunction, contributing to the understanding of the condition and potentially leading to better diagnoses and new treatments. Twelve [...]
Pancreatic Cancer Vaccine Shows Promise in Small Trial
Using mRNA tailored to each patient’s tumor, the vaccine may have staved off the return of one of the deadliest forms of cancer in half of those who received it. Five years ago, a [...]