In Vitro Drug Metabolism Profiling & Biotransformation Services

In the critical phases of hit-to-lead and lead optimization, researchers must map the complete metabolic fate of a New Chemical Entity (NCE). Standard targeted bioanalysis often misses unpredicted biotransformations because it requires prior knowledge of the target mass. When a molecule enters the hepatic system, it undergoes complex structural modifications—ranging from subtle oxidations to the addition of bulky endogenous conjugate molecules. Failing to identify these changes early can lead to the progression of molecules with poor metabolic stability or hidden toxicophores.

Our in vitro metabolism profiling utilizes an untargeted, high-resolution approach. By acquiring highly accurate mass spectra and distinct fragmentation patterns, we enable scientists to perform exact structural elucidation. We systematically track the parent compound as it converts into multiple downstream species, identifying the vulnerable "soft spots" on the chemical backbone.

Whether your molecule undergoes simple aliphatic hydroxylation, N-dealkylation, or extensive conjugation events, our ISO 17025 certified workflows guarantee that every mass shift and structural assignment is completely traceable, reproducible, and ready to support rigorous scientific decision-making in medicinal chemistry optimization.

Unlike routine concentration assays, metabolic profiling requires customized in vitro incubation and highly sophisticated mass spectrometry. We adapt our experimental design to the specific chemical properties and structural class of your molecule.

Microsomal and Hepatocyte Profiling Models

We deploy a variety of highly standardized in vitro biological models to simulate hepatic metabolism accurately. These models are carefully prepared and validated to ensure they retain optimal enzymatic activity, generating sufficient metabolite yields for confident downstream structural analysis.

• Liver Microsomes (HLM/MLM/DLM): Liver microsomes represent the gold standard for rapid metabolic profiling. These subcellular fractions contain concentrated levels of Cytochrome P450 (CYP) enzymes and Flavin-containing monooxygenases (FMOs). Because they are devoid of cellular membranes and competing physiological processes, microsomes provide a highly efficient, high-throughput environment to quickly identify major oxidative metabolites. They are also the ideal starting matrix to evaluate potential drug-drug interactions by monitoring the induction or inhibition of specific CYP isoforms.
• Cryopreserved Hepatocytes: While microsomes are excellent for studying CYP-mediated oxidation, intact cellular models like cryopreserved hepatocytes contain the complete, integrated suite of all hepatic drug-metabolizing enzymes (including UGTs and SULTs). They naturally retain all necessary endogenous cofactors. Hepatocyte profiling is absolutely essential for compounds that bypass primary oxidation and are directly cleared via extensive conjugation pathways, providing a comprehensive and physiologically relevant picture of in vitro clearance.

In-Depth Metabolite Identification (MetID)

Identifying the exact structure of a novel metabolite in a biological soup requires analytical precision far beyond nominal mass resolution. We provide in-depth drug metabolite identification using premier HRMS platforms.

• Sub-PPM Mass Accuracy for Elemental Composition: High-resolution instruments distinguish between molecules that share the same nominal mass but have different elemental compositions. By achieving sub-ppm mass accuracy, we calculate the exact chemical formula of unknown degradation products, immediately eliminating false positives.
• MS/MS Fragmentation Trees for Structural Localization: Knowing that a molecule gained an oxygen atom (+15.9949 Da) is not enough; researchers must know where the oxygen was added. By analyzing collision-induced dissociation (CID) patterns, we break the metabolite into specific fragment ions. By comparing these fragment masses against the parent drug's baseline fragmentation tree, we pinpoint the exact functional group or ring structure that underwent biotransformation.

Reactive Metabolite Screening (GSH Trapping)

Certain enzymatic biotransformations inadvertently generate highly reactive, electrophilic intermediates. Chemical species such as quinones, epoxides, and iminium ions are notorious for covalently binding to off-target cellular proteins and DNA, leading to severe idiosyncratic drug toxicity or immune-mediated liver injury.

Because these intermediates are highly unstable and transient, they cannot be detected directly by standard LC-MS/MS. Instead, we utilize specialized nucleophilic trapping agents during the in vitro incubation phase:

• Glutathione (GSH) Trapping: Used to capture "soft" electrophiles. The sulfhydryl group of GSH rapidly attacks quinones and Michael acceptors, forming a stable, highly polar GSH-conjugate that we can easily detect and characterize via HRMS.
• Potassium Cyanide (KCN) Trapping: Deployed to capture "hard" electrophiles, particularly transient iminium ions formed during the oxidation of cyclic amines, yielding stable cyano-adducts.

Capturing these adducts early in the discovery pipeline allows structural chemists to proactively redesign the molecule—such as adding a fluorine atom to block a vulnerable metabolic site—to mitigate downstream toxicity risks.

Extracting trace metabolite signals from the heavy background noise of a microsomal or hepatocyte incubation is a massive computational challenge. Biological matrices produce thousands of endogenous lipid, peptide, and small-molecule ions that can easily mask a low-abundance metabolite. Our data analysis pipeline is designed specifically to deconvolute complex HR-LC-MS/MS datasets.

• Mass Defect Filtering (MDF): Every element has a precise mass defect (the difference between its exact isotopic mass and its nominal integer mass). Parent drugs possess a unique mass defect "signature." Our bioinformatics software applies MDF templates to mathematically filter out thousands of endogenous matrix ions. The algorithm retains and highlights only those chromatographic peaks that share a similar mass defect range with your parent drug. This dramatically increases the signal-to-noise ratio and ensures trace-level metabolites are instantly isolated for review.
• Isotope Pattern Recognition: For synthetic NCEs containing halogen atoms (such as Chlorine or Bromine), our software automatically tracks their unique natural isotopic distributions (e.g., the distinct 3:1 ratio of 35Cl to 37Cl). The algorithm searches the entire full-scan dataset for these specific isotopic doublets, ensuring that no halogen-retaining metabolite is missed during automated peak picking, even at extremely low concentrations.
• Molecular Networking: We utilize advanced molecular networking to cluster structurally related MS/MS spectra together based on cosine similarity scores. By analyzing these spectral networks, our scientists rapidly deduce structural relationships between the parent drug and its downstream degradation products.

To ensure optimal in vitro incubation and maximum MS ionization efficiency, please adhere to the following submission guidelines. If your compound exhibits poor solubility or requires specific compound stability and degradation studies before incubation, please notify our technical team in advance.