GC Biopharma said Wednesday that its U.S. subsidiary ABO Plasma (formerly ABO Holdings) has opened the Laredo Plasma Center in Texas. The opening took place Tuesday, local time.
ABO Plasma will begin recruiting plasma donors immediately. Stored plasma has a shelf life of 24 months, and sales will commence once the U.S. FDA grants approval. The FDA approval process for plasma centers typically takes about nine months, and ABO Plasma aims to obtain approval in the first half of 2026.
Originally slated for completion in 2026, the Laredo Plasma Center’s launch was accelerated to meet growing demand for Alyglo and other plasma fractionation products. GC Biopharma also plans to open the Eagle Pass Plasma Center in Texas in 2026.
“This year will be a turning point for our domestic and global plasma fractionation business,” said GC Biopharma CEO Huh Eun-chul. “We are strengthening competitiveness through a stable supply chain.”
Alyglo, GC Biopharma’s flagship immunoglobulin product, is manufactured using 100 percent U.S.-sourced plasma. Under Executive Order 14257 on reciprocal tariffs, tariffs are applied only to non-U.S.-sourced raw materials if U.S.-sourced plasma accounts for more than 20 percent of the finished product. For Alyglo, plasma makes up around 50 percent of the product, excluding additives.
Related articles
- GC Biopharma wins FDA nod for 6th US plasma center in California
- GC Biopharma aims to sell $100 mil. Alyglo in US by 2025
- GC Biopharma returns to profit in Q1 on blood product gains, export growth
- GC Biopharma's blood product Alyglo wins IR52 Jang Young-shil Award
- GC Biopharma’s Alyglo is registered on 3 major US insurers’ formularies
- GC Biopharma files Korea IND for Covid-19 mRNA shot
- GC Biopharma lands CMO role on Curevo’s shingles shot CRV-101
- GC MS launches Korea’s 1st domestically produced powdered hemodialysis agent
- GC Biopharma wins Thai go-ahead for phase 3 two-dose chickenpox vaccine trial
- GC Biopharma marks record-high sales of ₩609.5 bil. in Q3
- GC Biopharma develops AI model to predict joint disease in hemophilia patients
