LabGenius Therapeutics will present preclinical data for LGTX-101, its AI-designed Nectin-4 x CD3 T-cell engager, at AACR 2026 in San Diego.
LabGenius Therapeutics, a drug discovery company that combines artificial intelligence (AI), high-throughput experimentation and machine learning to develop next-generation therapeutic antibodies, has announced that it will present a scientific poster at the AACR Annual Meeting 2026. The event will take place from 17–22 April at the San Diego Convention Center, California.
The poster will showcase preclinical data for LGTX-101, the company’s selectivity-enhanced Nectin-4 x CD3 T-cell engager (TCE), highlighting its potential as a targeted cancer therapy.
Targeted T-cell activation
According to the data, LGTX-101 demonstrated robust T-cell activation in primary bladder cancer co-culture models at concentrations below 5 pM. Importantly, the studies showed no evidence of T-cell activation when peripheral blood mononuclear cells (PBMCs) were cultured with human primary keratinocytes, which naturally express Nectin-4.
This selectivity suggests that LGTX-101 may effectively target tumour cells while sparing healthy tissues.
Tumour regression in preclinical models
In vivo studies using a humanised BT-474 xenograft mouse model showed robust and reproducible regression of established tumours. The researchers observed more than 90 percent tumour growth inhibition at dose levels as low as 0.1 mg/kg, demonstrating the potent antitumour activity of LGTX-101.
Additionally, preliminary pharmacokinetic data indicate that the antibody could support a clinical dosing regimen ranging from every two weeks to every four weeks, potentially offering a convenient schedule for patients in future trials.
Leveraging AI in drug discovery
LabGenius has emphasised the role of AI and machine learning in accelerating the development of next-generation antibody therapeutics. By integrating computational approaches with high-throughput experimentation, the company aims to design highly selective molecules capable of potent tumour targeting while minimising off-target effects.
The presentation at AACR 2026 will provide attendees with an opportunity to review the full dataset and explore the potential of AI-driven bispecific antibody design in advancing targeted cancer therapies.
The poster titled ‘A Novel Machine-Learning Derived Nectin-4 x CD3 Bispecific T-Cell Engager, LGTX-101, Demonstrates High Degrees of Tumour Selectivity and Potently Induces Tumour Regression in vivo’, will be presented on Monday 20th April 2026, from 09:00 to 12:00 PDT. It will be displayed in Section 10, Board 18 at the San Diego Convention Center.
