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Nearly a century ago, Alexander Fleming discovered a penicillin-producing mold. Over the following decades, various microbes were used to make a range of therapeutics, from insulin to vaccines. Although gene-editing and other techniques can improve the production of microbe-based biologics, artificial intelligence (AI) could push these drugs even further.

“Artificial intelligence and machine learning play a crucial role as transformative tools in pharmaceutical research and microbial engineering,” according to Ayaz Belkozhayev, PhD, associate professor in the department of chemical and biochemical engineering at Satbayev University in Kazakhstan, and his colleagues. “These technologies enable the analysis of large datasets, the optimization of metabolic pathways, and the development of predictive models.”

Plus, Belkozhayev’s team points out that AI-based technologies can be used to develop efficient microbes that provide sustainable production of biotherapeutics. These biotherapeutics include ones that battle largely drug-resistant microbes, such as Acinetobacter baumannii, which can infect a person’s blood, lungs, wounds, and more.

AI-based tools could also be applied to microbes that produce lipophilic compounds, such as modified antibodies or peptides. Nonetheless, Zhang Dawei, PhD, an investigator in synthetic biology and microbial manufacturing engineering at the Tianjin Institute of Industrial Biotechnology in China, and his colleagues explain that lipophilic compounds can accumulate in cell membranes during fermentation, which can decrease production or even kill the cells producing the biotherapeutic.

To address this membrane-capturing problem, scientists explore what Dawei’s group called “membrane engineering techniques to construct highly flexible cell membranes … to break through the upper limit of lipophilic compound production.” AI could play a key role in this process. As Dawei’s group notes: “With the continuous advancement of artificial intelligence technology in the field of biomedicine, computer-assisted scientific research will provide a more comprehensive blueprint for the construction process of highly flexible cell membranes.”

Nonetheless, AI alone will not make better microbes for producing biologics. As Belkozhayev’s team emphasizes, “Innovations in genetic engineering, synthetic biology, adaptive evolution, [machine learning], and high-throughput screening have led to substantial progress in optimizing microorganisms for the efficient production of complex biological and chemical compounds.”

So, as is often the case, no one thing is the solution to all of the challenges in making biotherapeutics from microbes. Still, AI will probably enhance this area of bioprocessing.

ATLANTA – The City of Atlanta will convene the first meeting of its newly formed Artificial Intelligence Commission on May 7 at 4 p.m. at Atlanta City Hall in the Larry Dingle Committee Room.

What we know:

The commission was established by legislation introduced in December 2024 by District 2 Council member Amir Farokhi and approved by the Atlanta City Council. The initiative aims to explore how artificial intelligence can enhance city operations, improve service delivery, and increase government efficiency.

The 13-member commission includes a mix of city leaders, academics, and technology experts. Current members include:

• Jason Sankey, Chief Information Officer, City of Atlanta
• Nikhil Deshpande, Chief Digital and AI Officer, State of Georgia
• Larry Williams, Technology Association of Georgia
• Donald Beamer Jr., appointee of Mayor Andre Dickens
• John Yates, technology policy and research representative
• Dr. Charlotte Alexander, Georgia Institute of Technology
• Dr. Joy Harris, Georgia State University
• Council member Amir Farokhi, appointee of Council President Doug Shipman
• Matthew Garver, representing Council Districts 1-4 and Post 1 At-Large

Four commission seats remain vacant, including representatives for Emory University, Atlanta University Center, and two additional district groupings.

The backstory:

Atlanta is just one of many cities that is currently exploring how to use AI within its government.

According to Cities Today, New York has implemented the AI Action Plan, which focuses on responsible AI governance across city agencies.

Boston has also created guidelines for responsible AI use, like ensuring transparency and accuracy in applications such as automated translation and chatbot services. The city also encourages safe spaces for experimentation.

The state of New Jersey has implemented a new AI translation service for applicants seeking unemployment assistance and other public services. It also has an active AI task force that is looking into other ways to use AI throughout the state. 

State and local governments in Arizona have implemented a variety of policies related to AI. It also created an AI steering committee to help inform future AI deployment and identify potential applications for its use, according to GovTech.com. 

San Jose in California was instrumental in launching the GovAI Coalition, which includes about 550 from across the United States. Its mission is to promote responsible and purposeful AI in the public sector. 

What’s next:

The commission is expected to provide guidance on how AI can be responsibly and effectively integrated into city services while addressing ethical and community concerns. The meeting is open to the public.

AtlantaNewsArtificial Intelligence

Artificial intelligence (AI) is reshaping health care delivery, and pharmacy practice is no exception. AI is streamlining workflow, enhancing patient care, and challenging pharmacists to redefine their roles. Although AI holds great promise, it also raises questions about future job security and regulatory frameworks.

As a pharmacist working in both retail and hospital settings, I’ve witnessed firsthand the pressures mounting in our field, including higher patient loads, greater clinical responsibilities, and increasing administrative tasks. Amid this complexity, AI is emerging as a powerful tool, offering the potential to alleviate some of the burdens we face while also enhancing our ability to provide quality care.

In the hospital environment, AI-driven tools are already proving valuable. Clinical decision support systems flag drug interactions and dosing errors in real time. Algorithms aid in antimicrobial stewardship by analyzing resistance trends and recommending targeted therapies.¹ In one hospital where I’ve practiced, AI models integrated into the electronic health record (EHR) predicted patient deterioration, prompting earlier interventions and improved outcomes.² These systems are far from perfect, but they represent a shift toward proactive, data-driven pharmacy.

In the retail pharmacy, the opportunities are just as impactful. AI-based platforms are helping automate refill workflows, prior authorizations, and even patient communication. Predictive analytics can identify patients at risk of nonadherence or potential complications. AI tools can also support OTC recommendations based on symptoms and medication history, freeing up pharmacists to focus more on counseling and clinical services.¹ I’ve personally seen how automation of insurance claim processing and smart inventory systems save hours of manual work every week.

Still, AI integration isn’t without challenges. One concern is data privacy, especially with cloud-based tools that interface with protected health information.³ There’s also the risk of bias in AI models, especially if they are trained on incomplete or non-representative data.⁴ Importantly, some pharmacists worry about losing their clinical intuition in favor of black-box suggestions that may not account for patient nuance. From my perspective, these concerns highlight the need for pharmacists to stay engaged in the development and testing of these tools.

Another barrier is cultural. In both hospital and retail settings, I’ve encountered pharmacists who are skeptical or even fearful of AI, viewing it as a threat rather than a resource. This hesitation can slow adoption and lead to missed opportunities. Pharmacists must be proactive in shaping the way AI is implemented in our field. That includes participating in pilot programs, advocating for clinical input in design, and embracing tech literacy as a core competency.

Ultimately, AI should be seen not as a replacement, but as a partner. It can take over repetitive and time-consuming tasks, but it can’t replace the nuanced clinical judgment, empathy, and patient relationships that define our profession. Pharmacists are uniquely positioned to guide AI integration in ways that protect patient safety and elevate our scope of practice.

About the Author

Alaa Abdul Ghani, PharmD, is a practicing pharmacist in both retail and hospital settings in Orlando, Florida. She is passionate about the intersection of health care and technology and is an advocate for pharmacists’ involvement in shaping the future of AI in pharmacy practice. She can be reached at abdulghani.a@icloud.com or 407-590-7756.

But this leads us to a pressing question: Will AI make the pharmacist obsolete?

The reality is more nuanced. Yes, AI will reduce the need for manual verification of low-risk prescriptions, and some laws may evolve to reflect that. But that doesn’t mean the pharmacist role will vanish. Instead, it will shift. Pharmacists who adapt by taking on more consultative, clinical, and interdisciplinary roles will thrive. Regulatory frameworks may change, but our relevance depends on how we respond to these innovations.

As AI continues to evolve, so must we. Rather than fear change, pharmacists should see this moment as an opportunity to lead, to innovate, and to reinforce the irreplaceable human element of healthcare.

REFERENCES

1. Raza MA, Aziz S, Noreen M, et al. Artificial intelligence (AI) in pharmacy: an overview of innovations. Innov Pharm. 2022;13(2):10.24926/iip.v13i2.4839. doi:10.24926/iip.v13i2.4839

2. Lauritsen SM, Kristensen M, Olsen MV, et al. Explainable artificial intelligence model to predict acute critical illness from electronic health records. Nat Commun. 2020;11:3852. doi:10.1038/s41467-020-17431-x

3. Murdoch B. Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Medical Ethics. 2021;22(122). doi:10.1186/s12910-021-00687-3

4. AI Algorithms Used in Healthcare Can Perpetuate Bias. News release. Rutgers Newark. November 14, 2024. Accessed April 30, 2025. https://www.newark.rutgers.edu/news/ai-algorithms-used-healthcare-can-perpetuate-bias

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