Producing Active Compounds from Medicinal Plants: Technologies and Challenges from Gene Discovery to Large-Scale Production
Finding genes does not resolve the production challenge
Improving production of active compounds from medicinal plants requires linking biosynthetic gene discovery to pathway validation and production process development. In a review published in the International Journal of Molecular Sciences, Zaman and Park outline approaches connecting functional genomics, gene editing, and synthetic biology, along with the remaining challenges. This literature review generated or analyzed no new data and should be distinguished from a study that experimentally demonstrates the performance of a new production platform.
Specialized metabolites in medicinal plants contribute to defense and environmental adaptation and also serve as resources for drug development. However, their biosynthetic pathways are complex, and the amounts accumulated vary with plant genetics and growing conditions. For some plants, genomic information and pathway characterization remain incomplete. Even when genes that may contribute to production are identified, their actual functions and effects on other metabolic pathways must be established.
Connecting gene discovery, pathway regulation, and culture technologies
The review explains the roles of different technologies using examples including Artemisia annua, cannabis, ginseng, and yew. RNA sequencing (RNA-seq) identifies candidate biosynthetic genes by comparing gene expression across tissues or growing conditions. Single-cell RNA-seq reveals expression differences among cell types that can be obscured by measurements averaged across whole tissues. Interpreting genomic, transcriptomic, and metabolomic information together aims to narrow down candidate relationships between gene activity and target-compound accumulation for validation.
Once a candidate’s function is confirmed, metabolic engineering strategies can be considered, such as increasing the expression of relevant genes or regulating competing pathways. CRISPR gene editing (CRISPR/Cas9) is a tool for modifying target genes, while synthetic biology can also be used to assemble plant-derived biosynthetic pathways in microbial hosts. The review introduces enzymes involved in oxidation and sugar attachment during ginsenoside biosynthesis in ginseng, along with prior examples of regulating related gene expression. These examples involve different targets and production systems, so they should not be interpreted as common achievements of a single platform.
The target medicinal compound must also be distinguished from a biosynthetic intermediate. The review’s table presents the semisynthetic route to artemisinin as a process in which yeast produces artemisinic acid, followed by chemical conversion. This differs from a production strategy in which microbes directly make the final medicinal compound. Plant cell suspension cultures and hairy root cultures are discussed as approaches that can be coupled with bioreactors in which nutrients, acidity, and temperature can be controlled.
Moving predictions and experimental results into industrial production
Artificial intelligence (AI) and machine learning can help predict gene–metabolite relationships from multiple omics datasets and select candidates for pathway regulation. The authors note that prediction accuracy depends on data quality, biological context, and environmental variation. Predicted relationships require experimental validation, including checks of whether they hold in other plants or under different cultivation conditions.
Scaling up production also remains unresolved. Pathway instability, low metabolic flux efficiency, and scale-up costs are identified as obstacles in microbial and cell-culture systems. Whether increases in compound levels observed in plants persist under variable cultivation conditions also remains to be tested. Use as a pharmaceutical raw material requires reproducible composition across batches, purification processes, and compliance with safety and quality standards.
The direction outlined by the review is to connect gene discovery, functional validation, production-host selection, and process optimization. Personalized plant-derived therapies are also discussed as a future research direction, but application in clinical care would first require pharmacological validation, dose standardization, and evidence of safety and clinical efficacy.
Source: Full review, paper DOI.
Plant Biotechnology, Published May 2026.
Summary: Resolving the historical supply bottlenecks and yield volatilities that have restricted the pharmaceutical translation of specialized plant metabolites, this comprehensive framework integrates functional genomics with scalable synthetic biology architectures. By optimizing high-throughput RNA sequencing matrices alongside artificial intelligence-assisted pathway predictions, the platform constructs discrete metabolic maps governing the synthesis of key bioactive leads. Utilizing target CRISPR/Cas9 gene editing protocols to execute precise metabolic engineering, researchers successfully redirected biosynthetic fluxes into high-performance yeast and heterologous expression systems. This programmatic intervention achieved robust yield improvement for medicinally critical inputs—including artemisinin, cannabinoids, ginsenosides, and taxol—advancing structural production velocity from micro-scale engineering setups into validated, scalable pilot plant operations.
Researchers and companies developing natural-product raw materials can assess experiments that increase target-compound content separately from the establishment of a stable manufacturing process. For example, developing a ginsenoside production process would involve validating candidate-enzyme functions, evaluating whether plant cell culture or a microbial host is the more suitable system, and checking compound composition and production stability across repeated cultures. If an intermediate is produced, the downstream process for converting it into the final compound must also be assessed. This approach could reduce reliance on wild harvesting and improve supply stability. However, the review does not directly demonstrate cost reductions or success at industrial scale, so each process requires validation that includes purification costs, batch reproducibility, and quality specifications.