Tag Archives: Moorehouse School of Medicine

Are Acidic Cannabinoids the Next Frontier for Product Innovation?

By Pam Chmiel
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While the cannabis industry has made significant strides in incorporating minor cannabinoids into product formulations, a vast number of therapeutic compounds remain largely unexplored. Researchers and cannabis physicians have been experimenting with acidic cannabinoids for several years with promising results, but the broader industry is only now beginning to catch up. As extraction technologies improve and research advances, more acidic cannabinoids are appearing in new product formulations.

“People are more and more focused on acidic cannabinoids now because, before, we did not have the advanced extraction technology to isolate them in a highly purified form, and now we do,” said Hemant Kumar Bid, PhD, program director for the Master of Science in Biotechnology at Morehouse School of Medicine, where he focuses on medical cannabis.

“The plant produces cannabinoids in their acidic form,” Bid explained. “These acids are the precursors to neutral cannabinoids such as CBD and THC.”

Among the acidic compounds, Bid has a particular affinity for cannabigerolic acid (CBGA), often referred to as the “mother of all cannabinoids.”

“In the scientific world, we call it the stem cell,” he said. Stem cells are extremely powerful because they can develop into many different types of cells in the body. CBGA works in a similar way in the plant.

CBGA is the foundational precursor molecule from which the plant synthesizes other major cannabinoids. In the glandular trichomes of the cannabis plant, enzymes convert CBGA into THCA, CBDA, and other downstream compounds that later become THC, CBD, and CBG when heat triggers decarboxylation.

Bid noted that emerging research suggests that acidic cannabinoids may possess unique therapeutic properties and operate through molecular mechanisms distinct from those of their neutral counterparts (e.g., THC, CBD). Some early findings indicate that these compounds may even outperform their decarboxylated forms. For example, he cited research from Johns Hopkins University suggesting that acidic cannabinoids may demonstrate significantly higher bioavailability in some formulations.

Scientific understanding of the endocannabinoid system is also expanding rapidly. Early research focused primarily on CB1 and CB2 receptors and two endogenous ligands, anandamide and 2-AG. Today, scientists recognize that the system is far more complex.

“Initially, people thought CB1, CB2, and the two molecules were the only triggers,” said Bid. “But that is not the case. It is the whole ocean now. There are so many receptors, signaling molecules, and enzymes that we still have yet to discover.”

One of the biggest obstacles to harnessing acidic cannabinoids is their chemical instability. Exposure to heat, light, oxygen, or simply the passage of time causes decarboxylation. In this process, THCA converts to THC, CBDA to CBD, and CBGA to CBG, making it difficult to preserve the original acidic molecules.

 

Emerging Research on Acidic Cannabinoids

A recent scientific review published in the National Library of Medicine highlights the therapeutic potential of the four primary naturally occurring acidic cannabinoids: THCA, CBDA, CBGA, and CBCA.

Rather than acting primarily through CB1 receptors like THC, these compounds appear to influence a wide range of molecular targets. Researchers have observed activity across several biological pathways, including serotonin receptors (5-HT1A), inflammatory enzymes such as COX-2, PPARγ nuclear receptors involved in metabolic regulation, TRP ion channels, and intracellular calcium signaling systems. Some studies also suggest interactions with enzymes linked to neurodegenerative disease, including BACE-1 and cholinesterases.

This multi-target activity has led scientists to explore acidic cannabinoids across several therapeutic areas. In neurodegenerative disease models, they have been shown to reduce amyloid-beta accumulation, regulate calcium signaling in neurons, decrease neuroinflammation, and improve learning and memory performance in animal studies. In inflammation models, THCA and CBDA demonstrated COX-2 inhibition and PPARγ-mediated anti-inflammatory activity, reducing joint swelling and cartilage damage in arthritis research.

Early oncology studies have also identified anti-migratory and anti-proliferative effects in aggressive cancer cell lines, along with signaling pathways associated with anti-metastatic activity. In epilepsy models, CBDA has been shown to increase seizure thresholds, particularly when formulations improve central nervous system exposure.

Researchers note that pharmacokinetics remain one of the major hurdles. Acidic cannabinoids tend to absorb quickly but often exhibit short half-lives and relatively limited brain penetration due to the carboxyl group in their molecular structure. As a result, formulation science and delivery systems may be just as important as the compounds themselves.

Although human clinical trials remain limited, advances in stabilization, encapsulation, and delivery technologies are beginning to make these fragile compounds easier to study. As a result, scientists increasingly believe that preserving cannabinoids in their native acidic form could open the door to a new generation of targeted cannabinoid therapeutics.

 

Doctors Prescribing Acidics

One of the well-known cannabis physicians paving the way for understanding treatments is Dr. Bonni Goldstein. She started her cannabis medicine practice, Canna-Centers, in California in 2011, and later added Goldstein Wellness, an educational platform designed to educate healthcare professionals.

Long before the surge of interest in CBD sparked by Charlotte Figi’s story, Goldstein had been exploring acidic cannabinoids in her clinical work. In the early years of her practice, she began experimenting with THCA, particularly in pediatric patients whose parents were seeking non-intoxicating options. At the time, very little clinical data existed on acidic cannabinoids, but anecdotal results suggested that THCA could offer therapeutic benefits without the psychoactive effects associated with THC.

The pediatric side of her practice expanded significantly after the CNN documentary featuring Dr. Sanjay Gupta aired, highlighting the remarkable impact CBD treatment had on Charlotte Figi, a young patient with severe epilepsy. While some evidence suggested that seizures and autism exhibit high levels of neuroinflammation, “We didn’t really know a lot about CBDA then, but there was evidence in preclinical studies that these compounds may reduce inflammatory signaling, which then leads to fewer seizures and unwanted behaviors in children who have autism,” said Goldstein.

“Everyone’s endocannabinoid system expression level is different,” she explained, noting that cannabinoid therapies frequently require individualized approaches to dosing and formulation. There is no standardized dose or standardized medicine for cannabis.

Goldstein likes to layer cannabinoids in her treatment depending on the patient’s unique needs, since everyone is different and responds differently to treatment. She added that CBD interacts with over 75 targets in the brain and body, whereas CBDA is more selective; it has its own targets, but also overlaps with CBD.

Goldstein has recently been incorporating CBDA into patients’ regimens who have seizures because there is some evidence of its anticonvulsive properties. She cited a small study of 14 kids with autism in Australia, claiming that a CBDA-dominant botanical formulation achieved significant success for 93% of participants. “It’s a very small study, but it’s very promising,” she said. She has also begun layering CBGA into her treatments due to its anti-inflammatory and anticonvulsant potential.

As clinicians and researchers continue to explore acidic cannabinoids, physicians are beginning to consider how these compounds may fit into tailored treatment strategies for specific medical indications.

 

Product Development Challenges

Acidic cannabinoids are minor cannabinoids, meaning the plant naturally produces them in relatively small amounts. Extracting meaningful quantities often requires significantly larger volumes of biomass.

Gene editing technologies may offer a potential solution, though they entail both scientific and economic trade-offs. Techniques such as CRISPR-Cas gene editing allow researchers to manipulate genes involved in cannabinoid biosynthesis, potentially increasing the plant’s production of specific acidic compounds.

“We have the power of CRISPR-Cas technology, which is a very advanced gene editing technology,” said Bid. “We can manipulate genes encoding acidic cannabinoids, overexpress them, and create hybrid plants that produce larger quantities for research.”

“However, when you manipulate nature’s backbone, it becomes disturbed and weakened,” Bid explained. “The plant can become more susceptible to fungi, bacteria, mold, and mildew.” A manipulated plant may remain viable for only five or six generations before failing entirely, creating a significant challenge for patients and clinicians trying to replicate their formulations.

There is one notable advantage. Acidic cannabinoids are more polar than their neutral counterparts. This can make them easier to formulate into certain delivery systems and may improve bioavailability compared with their fat-soluble neutral counterparts. Lower doses could also make products more affordable for patients or consumers.

 

Extraction Technologies

The volatility of acidic cannabinoids has made them difficult to extract and preserve.

“The trick is to avoid heat and use a cold process,” Bid explained.

Many solvent-based extraction systems, including ethanol, CO₂, and hydrocarbon systems, can be adapted to operate at very low temperatures; however, mechanical extraction methods produce higher-quality, full-spectrum results while preserving acidic compounds.

“The most popular method is mechanical expression, such as rosin or ice water hash,” Bid said. “With ice water extraction, there is no heat involved so that acidic cannabinoids can be retained in a carefully controlled environment.”

Essentia Scientific, where Bid serves as a scientific advisor, uses large-scale aqueous washes to solubilize acidic cannabinoids directly from plant material. The process involves sequential filtration steps to remove suspended solids and produce a clarified extract.

More advanced technologies are also entering the field. Cryogenic extraction and ultra-low-temperature processing systems are being developed specifically to preserve temperature-sensitive cannabinoids. Another emerging approach is alkaline leaching, a greener technique that extracts acidic cannabinoids at a high pH. This method avoids lengthy drying steps that can accelerate decarboxylation.

Additional innovations include crystallization and encapsulation technologies. In crystallization processes, acidic cannabinoids are stabilized within structured lattices such as crystalline salts or sugar alcohol matrices.

One company working in this area is LipidBond, which holds patents on an encapsulation system designed to protect cannabinoids from light, oxygen, and heat. The technology uses nanoencapsulation strategies that are common in pharmaceutical development but relatively new to cannabis processing. By packaging cannabinoids inside nanoparticles, the system can help stabilize the molecules and potentially increase bioavailability by enabling them to cross the blood-brain barrier.

“If I have a client who wants 75 percent acidic compound and 25 percent non-acidic compound, I have a formula for that,” said Bobby Lafferty, Chief Technology Officer at LipidBond, who designed the company’s processing equipment. “It is essentially a matter of adjusting temperature and pressure. Once you can pinpoint those variables, you can control the exact decarboxylation rate.”

Lafferty says extensive research and development have helped the company understand how cannabinoids interact during processing.

“We have done so much R&D that we know how everything works together,” he said. “If I look at a COA and see 28 percent THC or 30 percent CBD, I can design the compound around that profile.”

The system functions as a microemulsion platform that maintains full-spectrum plant components.

“Our process is essentially an emulsion system,” Lafferty explained. “Not nano emulsions but micro emulsions that are extremely stable. When you keep the plant full spectrum, there are fibers and other natural compounds that act as emulsifiers and help prevent cannabinoids from falling out of suspension.”

In addition, the increasingly common practice of flash freezing and processing fresh frozen cannabis immediately after harvest is helping preserve cannabinoids and terpenes in their original acidic form.

 

Shelf Stability Requires Cold Storage

Even after extraction, maintaining the stability of acidic cannabinoids remains challenging because they naturally decarboxylate over time.

Researchers are also developing formulation stabilizers specifically for acidic cannabinoids. One patented composition, according to Bid, combines an acidic compound with a pharmaceutical-grade solvent to achieve room temperature stability for nearly 24 months.

“Advanced low temperature extraction, gentle processing, and stabilization strategies are what will drive success for future acidic cannabinoid formulations,” said Bid.

Several companies are already exploring stabilized acidic cannabinoid formulations, suggesting the next wave of cannabis product innovation may focus on preserving the plant in its raw biochemical state.

As extraction technologies improve and stabilization techniques advance, acidic cannabinoids may represent one of the most promising frontiers in cannabis product innovation.

 

 

 

The Power of AI and How it Will Transform Cannabis Medicine

By Pam Chmiel
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Biotechnology, cannabis medicine, and the rapid advancements in artificial intelligence (AI) and machine learning (ML) are beginning to converge.

Hemant Kumar Bid, program director for the Master of Science in Biotechnology and the Medical Cannabis concentration at Morehouse School of Medicine, believes this convergence could dramatically accelerate the development of cannabis-based therapies. With AI, cannabis medicine may move beyond today’s trial-and-error approach toward more personalized, precise treatments.

Biotechnology combines biological science with advanced technology to develop medical solutions, including drug discovery, genetic engineering, and diagnostic tools. “Modern biotechnology focuses on molecular biology, genetic engineering, and advanced cell culture techniques. This is where it will advance cannabis medicine,” explains Bid.

 

The Foundational Elements of AI and Machine Learning

AI and machine learning are closely related but serve distinct roles.

AI refers to computer systems designed to perform tasks that usually require human intelligence, such as reasoning, pattern recognition, and decision-making. Machine learning, a branch of AI, identifies patterns in large datasets, improves as it processes more data, and predicts future outcomes.

Many AI systems rely on deep learning, a method using neural networks to detect complex patterns across massive datasets. Another important capability is natural language processing (NLP), which allows computers to understand and generate human language and analyze vast bodies of scientific literature, uncovering insights and connections that might otherwise take researchers years to identify.

Machine learning is already widely used in biotechnology to analyze complex biological data and predict how molecules behave in the body.

 

AI in Drug Discovery and Development

AI is rapidly transforming how new drugs are discovered and developed.

Traditionally, drug discovery depends heavily on animal models and laboratory testing—a slow, expensive trial-and-error process. Machine learning can now analyze large molecular datasets to predict which cannabinoid compounds interact with specific receptors, such as CB1, CB2, TRPV1, GPR55, and serotonin receptors. This capability can significantly reduce both the time and cost of traditional drug discovery.

AI can also predict toxicity and safety risks in drug formulations before human testing begins. “Once a clinician knows that toxicity will exceed 70%, they can decide not to move forward,” says Bid.

In addition, NLP tools can mine extensive cannabis research literature to identify emerging therapeutic targets and gaps in current studies.

 

Personalized Cannabis Medicine

Many diseases are complex, and scientists are still uncovering their underlying causes. Conditions such as cancer may be influenced by a combination of genetics, lifestyle, and environmental factors.

Deep learning systems can analyze pathology images and genetic data at a level beyond human capability. They can detect subtle changes in DNA, RNA, or protein structures that influence disease progression and treatment outcomes. These insights are opening the door to how personalized approaches can be applied to cannabis medicine.

Machine learning models are already being applied to pharmacogenomic data to predict how a patient will metabolize cannabinoids based on genetic variation, particularly in liver-metabolizing enzymes like cytochrome P450, which play a key role in metabolizing THC and CBD.

“That means this genomics and pharmacogenomics approach, using machine learning models, could help predict efficacy and adverse effects before treatment begins,” says Bid.

AI and ML systems can also analyze genetic mutations, disease risk, and patient data to suggest individualized treatment plans. Factors such as genetics, medical history, symptoms, prior cannabis use, disease severity, and previous treatment responses can all inform personalized decisions. Because everyone’s DNA and endocannabinoid system differ, a one-size-fits-all approach to cannabis medicine is ineffective.

 

Identifying Endocannabinoid Dysfunction

Bid emphasizes that more genetic research is needed to understand how the endocannabinoid system varies across populations worldwide. Without sufficient patient data, it is difficult to identify patterns of endocannabinoid dysfunction or determine which cannabis treatments are most effective.

Mobile applications like Strainprint are already tracking cannabis use and therapeutic outcomes, collecting valuable real-world patient data. These platforms can generate large datasets on dosing, product type, symptoms, and treatment results. AI can use this data to predict treatment response and support personalized medicine.

Such datasets may also help researchers identify patterns of endocannabinoid dysfunction and develop needed standardized diagnostic tools.

Today, many cannabis physicians still rely on trial and error when determining dosing and treatment protocols. AI-driven analysis of large patient datasets could dramatically accelerate the development of evidence-based guidelines.

 

Connecting Microbiome Insights

Emerging research increasingly links the gut microbiome to a wide range of diseases. AI-driven microbiome analysis, paired with endocannabinoid profiling, can identify biomarkers of gut health and guide interventions—from dietary modifications and probiotics to customized cannabinoid formulations.

Since most cannabinoid receptors reside in the gut, endocannabinoid deficiencies often intersect with microbiome imbalances. This integration highlights the importance of combining microbiome and endocannabinoid insights for effective treatment.

 

AI for Cannabis Safety and Patient Monitoring

AI applications in electronic health records and patient-reported databases can accelerate the detection of adverse effects associated with cannabis use. Traditional pharmacovigilance methods can take months or years to identify safety signals, but AI-driven analytics can flag potential risks in near real-time. This allows healthcare providers to optimize treatment plans, mitigate harm, and make data-driven decisions.

 

Transforming Clinical Trials

Clinical trials are the gold standard for evaluating new medicines and are required for FDA approval. Yet they remain costly, time-consuming, and often slow the development of innovative therapies.

AI can identify patients most likely to respond to specific treatments, improving trial success rates while reducing costs and timelines. By accelerating clinical trials, AI could speed the development of standardized cannabis medicines, strengthen regulatory oversight, and bring safe, effective therapies to patients faster.

 

AI and Cannabis Plant Science

Advances in plant science are shaping the future of cannabis medicine. Researchers now understand much of the cannabis genome and the biosynthetic pathways that produce cannabinoids, terpenes, alkaloids, and flavonoids. Breeders and cultivators have the ability to manipulate these pathways to achieve precise therapeutic outcomes.

New cannabinoids are being discovered faster than physicians can test and integrate them into treatment plans. Because cannabis plants are highly variable in their chemistry, AI could bring precision and consistency to breeding and cultivation. Machine learning models trained on spectroscopic data can predict cannabinoid and terpene content without the need for extensive lab testing.

“Since the plant is highly variable in its chemistry, we need AI to ensure precision and consistency in breeding and cultivation,” says Bid.

 

The Need for Data and Expertise

Despite the need for AI-driven cannabis medicine, large-scale datasets required to train effective machine learning models remain limited. And relatively few physicians have formal training in cannabis medicine.

Meanwhile, the pace of cannabinoid discovery in plant science continues to accelerate, widening the gap between scientific knowledge and clinical practice.

 

Potential Risks and Ethical Considerations

While AI offers enormous potential, it also raises important ethical and practical concerns. Large healthcare datasets pose privacy and data-breach risks, and implementing advanced AI systems can be expensive and energy-intensive.

As the cannabis industry integrates biotechnology and AI, careful attention is needed to ensure these technologies are deployed responsibly, safely, and equitably.

 

“Everything starts with education,” Bid emphasizes. By training the next generation of scientists and practitioners, the field of biotechnology and medical cannabis can fully leverage AI and ML—from precision cannabinoid medicine and endocannabidomic profiling to microbiome integration, accelerated drug discovery, and AI-guided patient monitoring. Introduction to these tools will prepare future leaders to innovate, expand applications, and advance AI-driven precision medicine in the cannabis industry.