AI Discovers Potential Drug for Malaria and Osteoporosis
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In what is becoming increasingly routine in pharmaceutical research, researchers have harnessed an artificial intelligence algorithm to pinpoint a compound, currently utilized in the treatment of malaria, that exhibits the capability to effectively counteract bone degeneration associated with osteoporosis.
The compound, dihydroartemisinin (DHA), is sourced from the indigenous Asian plant Artemisia annua L., commonly recognized as sweet wormwood or sweet sagewort. This plant has a longstanding history in traditional Chinese medicine, spanning over 2,000 years.
Predicting Small-Molecule Drug Effectiveness for Osteoporosis Gene Expression
A substantial collaboration led by researchers from Peking University School and Hospital for Stomatology and Peking University International Cancer Center in Beijing has utilized their previously designed deep-learning algorithm. Their goal was to predict the effectiveness of various small-molecule drugs in reversing specific gene expression related to osteoporosis.
In this instance, their focus was on bone marrow mesenchymal stem cells (MSCs). They applied the AI algorithm to profiles of both newborn and aged mice and pinpointed DHA as one of the top-ranking compounds.
Bone marrow MSCs serve as precursors to osteoblasts, which are responsible for bone tissue formation. However, in osteoporosis, these stem cells deviate from their normal differentiation into osteoblasts, transforming into fat-producing cells instead. Consequently, osteoclasts, which contribute to bone loss, become dominant.
Prioritizing Bone Marrow MSC Function Restoration for Osteoblast Supply in Bone Repair
The researchers emphasized the importance of restoring the functions of bone marrow MSCs since they continuously supply osteoblasts for bone repair.
In a mouse study, DHA-loaded nanoparticles were administered to mice with induced osteoporosis over a six-week period. Following this treatment, it was observed that the expected bone loss had significantly diminished, and the bone structure was nearly completely preserved.
“They pointed out that they designed mesoporous silica nanoparticles (MSNs) coupled with bone-targeting alendronate (ALN) to deliver DHA, aiming to enhance the therapeutic effectiveness of DHA in treating osteoporosis.”
ACS Cent. Sci. 2023
In subsequent experiments, the team observed that DHA effectively interacted with bone marrow mesenchymal stem cells (MSCs), preserving their ‘stemness‘ and ensuring their continued differentiation into osteoblasts. Additionally, DHA exhibited no signs of toxicity, positioning it as a highly promising and safe therapy for osteoporosis.
The researchers highlighted that current standard medications for osteoporosis, like estrogens and bisphosphonates, primarily address hormone deficiencies or bone resorption but do not directly restore the stemness and vitality of bone marrow MSCs.
In a broader context, the utilization of artificial intelligence to repurpose existing drugs for novel treatments is a rapidly expanding field within medical research. Small-molecule drug discoveries are leading the way in this endeavor.
AI-First Approach in Biotech
A study from the previous year detailed that biotech companies were adopting an ‘AI-first‘ approach in research, with over 150 small-molecule drugs already in the discovery stage, including 15 in clinical trials. Apart from being highly cost-effective, AI-assisted drug discovery research has the potential to significantly expedite the approval process for new life-saving medicines, emphasizing the importance of timely approvals.
AI has already led to the development of potential treatments for conditions like obsessive-compulsive disorder (OCD) and idiopathic pulmonary fibrosis (IPF, a type of lung disease) that are now advancing through clinical trials.
Recently, researchers at the University of Cambridge introduced Polymatheic AI, a machine learning model designed to aid in discoveries across various domains that might otherwise be missed by specialists focused on specific disciplines.
Read the orginal article on: New Atlas
