FUJIFILM Wako Chemicals Europe GmbH

CertiPro Series are product series of pharmaceutical raw material that complies with GMP with process validation. Process validation secures quality stability from batch to batch, and our well organised quality assurance team maintains high reliability in the market. 

PYROSTAR™ Neo is a new endotoxin detection reagent developed by recombinant technology.

PYROSTAR Neo is a lyophilized reagent that combines 3 recombinant factors (factor C, factor B, proclotting enzyme) with sequences derived from Limulus polyphemus and a chromogenic substrate (peptidyl pNA).The...

Sodium Dextran Sulfate 5000 suitable for pharmaceutical field with high quality.

This is high quality Sucrose with low endotoxin (0.2EU/g) originally from Hokkaido Japan. The specification criteria meets Japanese Pharmacopeia that can safely use in Pharma industry.

WakoVAC is FUJIFILM Wako Pure Chemical's Serum Free Cell Culture Media Series ​for Vaccine Production​.The lineup includes for MDCK cells, Vero cells and Insect cells.A series of media with very high performance in cell growth. We are especially aiming to support vaccine manufacturing with our quality...

OSAKA, Japan – May 11, 2023 – FUJIFILM Wako Pure Chemical Corporation (President: Koichi Yoshida) is pleased to announce the launch of its Good Manufacturing Practice （GMP）-compliant ROCK inhibitor*1 “Y-27632 for industrial cell culture applications. Y-27632 offered by FUJIFILM Wako Pure Chemical Corporation is compliant with the ICH-Q7 GMP for active pharmaceutical ingredients,*2 and is designed for commercial manufacture of cell therapy products using human induced pluripotent stem cells (hiPSCs).

AI-AAM (drug2drug®)

Drug2drugs is a service to provide you multiple active compounds with different scaffolds from only the structural information of one active compound without knowing the target protein, so that we can increase the overall success rate of clinical drug development.

Fujifilm has developed AI-AAM® (AI-Amino-Acid Mapping), a new scaffold transformation method based on AI and chemical simulation, with the aim of increasing the number of active compounds with various scaffolds from one active compound.

Scaffold transformation using AI-AAM requires only the structural information of an active compound, not the information of the target protein.