Ajay Gannerkote, President, Integrated DNA Technologies examines how AI is helping to advance the drug discovery landscape.

In the past decade, few fields in biotechnology have evolved as dramatically as gene synthesis and genome engineering.  The evolution of digital technologies, particularly the advent of artificial intelligence (AI), has resulted in a convergence whereby digital tools and AI are increasingly pivotal to the development of synthetic biology and precision medicine. As machine learning (ML) algorithms become more sophisticated and tools like Google DeepMind’s AlphaFold2 and generative design platforms become accessible, the drug discovery landscape is being redrawn. 

Today, AI is not only augmenting scientific analysis—it is reshaping how we design, build, and interpret the molecular machinery of life. From designing gene-editing components with mathematical precision to predicting protein functions and navigating biosecurity risks, AI is both the engine and compass of modern biotechnological innovation. It is propelling synthetic biology forward—generating innovations to revolutionize gene synthesis and genome editing. At the same time, use of these technologies is raising pressing biosecurity concerns that come with such powerful technologies. 

AI and genomics converge to drive precision medicine 

AI’s most disruptive contribution to genomics lies in its ability to decipher complexity and aid in target identification. As precision medicine moves to the forefront of drug development, AI is enabling researchers to extract actionable insights from terabytes of genetic and phenotypic data. ML models can now cluster disease subtypes, predict individual responses to treatments, and reveal biomarkers once buried in biological noise. 

These capabilities have transformative implications. For example, in the realm of antisense oligonucleotide (ASO) therapies, which target RNA to regulate gene expression, AI dramatically reduces the screening burden. Traditionally, identifying the optimal sequence required testing dozens to hundreds of candidates. Today, AI-powered analysis of patient data can pinpoint pathogenic mutations and predict which ASO designs will likely be most effective—cutting development time from months to weeks.  

Such accelerated timelines are essential for n-of-1 therapies, customised treatments for patients with ultra-rare diseases. Here, each day matters, and AI serves as a critical decision-making partner. These advances also rely on high-quality, specialized tools and reagents that enable rapid iteration. It is with this in mind that Integrated DNA Technologies (IDT) has continuously innovated on its portfolio, from short oligonucleotides to full-length synthetic genes, and gene editing systems tailored for both high-throughput screening and clinical-grade applications, all with the aim of helping partners and customers accelerate the pace of genomics and drive the AI-genomics revolution. 

For example, IDT’s collaboration with a cutting-edge human phenome project that integrates high-content imaging and AI to uncover new drug targets. Using more than 100,000 of IDT’s CRISPR libraries, the project conducts genome-wide knockout experiments, editing one gene at a time across thousands of human cells. High-resolution imaging tracks cellular responses, and AI models analyse the data to map gene-disease relationships.  

IDT also partners with researchers worldwide to share knowledge and expertise regarding CRISPR technologies, including the synthesis of CRISPR components such as clinical grade guide RNAs. Applying a next generation sequencing platform to screen for off-target profiles in multiplex, IDT develops platform methods for assessing the safety of CRISPR-based therapies. These efforts help to accelerate the development of CRISPR-based therapies. 

Precision meets performance with AI-optimised CRISPR-based synthetic biology 

Gene editing has become synonymous with CRISPR-Cas9, but precision and safety remain top priorities—particularly in therapeutic contexts where off-target effects (OTEs) could have serious consequences. High-content CRISPR screens exemplify how AI and high-throughput screening are driving innovation. These screens rely on highly precise gene editing components, particularly the Cas9 enzyme. The Alt-R HiFi Cas9 enzyme was developed after testing more than 250,000 Cas9 variants, resulting in a high-fidelity nuclease that dramatically reduces OTEs without sacrificing on-target editing efficiency. It has already shown clinical promise, successfully correcting the mutation that causes sickle cell disease in human haematopoietic stem cells with minimal genomic collateral damage. 

Complementing the editing system is IDT’s rhAmpSeq CRISPR Analysis System, a powerful multiplexed amplification protocol that accelerates data generation and allows researchers to quantify both on- and off-target effects across dozens or even hundreds of sites. The system’s RNase H2-activated primers and improved specificity make it an indispensable tool in analysing CRISPR-based therapeutics like CAR-T and CAR-NK cell therapies, where even minor genomic inaccuracies can have profound effects.  

Beyond gene editing, synthetic biology is experiencing a renaissance driven by AI-aided design. Assembling genes and entire pathways is no longer a manual, trial-and-error process. Instead, platforms now offer intelligent sequence modeling, optimization, and automated DNA synthesis services to turn digital designs into physical molecules rapidly. IDT’s custom DNA synthesis services are widely used to construct metabolic pathways, biosensors, and even synthetic chromosomes. For complex constructs, AI-assisted platforms can pre-screen for synthesis barriers like high guanine and cytosine (GC) content, secondary structures, or repetitive elements, then adjust sequences via codon optimisation or motif scrambling to ensure functional expression. 

DNA assembly methods such as Golden Gate and Gibson Assembly are further enhanced by predictive modeling, which allows researchers to design scarless, seamless junctions with higher fidelity. This has proven invaluable for researchers who are engineering pathways in microbes for biofuel production, vaccine development, and agricultural genomics, where modularity and precision are key. In the agriculture sector, for instance, gene synthesis is being used to introduce traits like drought resistance, nutrient-use efficiency, and pest tolerance into crop genomes. By correlating genetic variants with phenotypic traits via AI, researchers can design and synthesize optimized alleles in silico—then test them in plants with a turnaround time that was unthinkable a decade ago. 

Manufacturing for a global genomic future from bench to bedside 

AI and ML promise speed, but consistent, scalable production remains a cornerstone of translational success. IDT’s global manufacturing footprint—including facilities in the US, Belgium, and Singapore—supports rapid delivery of research- and clinical-grade materials. The company’s current Good Manufacturing Practice (CGMP) capabilities enable seamless transitions from discovery to clinic. The same oligonucleotide that helps measure a therapeutic target can later be scaled for use in human trials, accelerating the regulatory and commercial path. 

Furthermore, our consultative approach—working alongside academic laboratories, biopharma companies, and public health agencies—ensures that our reagents and protocols are aligned with real-world needs. During the COVID-19 pandemic, our PCR and CRISPR tools were crucial in tracking and characterising viral variants, highlighting how agile manufacturing and collaborative partnerships can meet urgent global demands. 

Biosecurity and the dual-use of AI- and genomics-driven synthetic biology 

As synthetic biology becomes more democratised through AI, biosecurity risks grow alongside the benefits. In 2024, the Nobel Prize in Chemistry was awarded for innovations in AI-driven protein structure prediction, including Google DeepMind’s AlphaFold2. These tools enable the rapid design of protein therapeutics—but could also be misused to model virulent proteins or engineer novel pathogens. 

To explore this risk, Microsoft’s Eric Horvitz partnered with IDT to evaluate the robustness of biosecurity screening tools used by nucleic acid synthesis providers. Their findings revealed gaps: Common screening tools failed to detect altered DNA sequences encoding synthetic proteins of concern. While software patches improved detection, the ¹ highlighted a need for ongoing vigilance. In a broader assessment involving multiple providers and screening platforms, some systems showed better performance—but the results varied. The conclusion was clear: Biosecurity screening tools must be continuously stress-tested and improved to remain effective against evolving threats. 

Organisations like the International Gene Synthesis Consortium (IGSC) are playing a pivotal role in this effort. Their Harmonized Screening Protocol² provides a shared framework for gene synthesis companies to screen customers and sequences, balancing innovation with security. But the onus does not lie solely on synthesis companies. Regulatory bodies, public agencies, software developers, and civil societies must align to strengthen the biosecurity ecosystem. AI can accelerate discovery—but without ethical guardrails and resilient safeguards, the very tools advancing human health could be turned against it. 

Looking ahead: Intelligence, innovation, and responsibility 

The convergence of AI and synthetic biology marks a new era for the life sciences—one defined by scale, precision, and possibility. From real-time disease surveillance and personalised gene therapies to climate-resilient crops and programmable cell therapies, the breakthroughs made possible through AI-enabled workflows are rewriting the boundaries of biological innovation. Together with our partners, we hope to exemplify what is possible when cooperative expertise, high-quality reagents, automated platforms, and intelligent design tools converge. These technologies are not only powering discoveries—they are supporting the infrastructure that makes those discoveries reproducible, safe, and translatable. 

Yet with enhanced power comes the need for collective responsibility. Industry, academia, and regulators must collaborate to ensure that synthetic biology remains a force for good—empowering cures, not conflicts. The promise of AI in drug discovery and genome engineering is profound. But it will take technical excellence, ethical foresight, and global cooperation to fully realize this future—where every base pair is a building block of progress, and every innovation is safeguarded for the benefit of all. 

References

1: https://www.biorxiv.org/content/10.1101/2024.12.02.626439v1

2: https://genesynthesisconsortium.org/wp-content/uploads/IGSC-Harmonized-Screening-Protocol-v3.0-1.pdf

Disclaimer: Alt-R™ HiFi Cas9, rhAmpSeq™ CRISPR Analysis System and IDT custom DNA synthesis services are for research use only. Not for use in diagnostic procedures. Unless otherwise agreed to in writing, IDT does not intend these products to be used in clinical applications and does not warrant their fitness or suitability for any clinical diagnostic use. Purchaser is solely responsible for all decisions regarding the use of these products and any associated regulatory or legal obligations.