Physiological hepatic in vitro systems
What we offer
Quality
Most extensively characterized 3D spheroid system on the market.
Unmatched predictive accuracy. Proven 100% specificity and 69% sensitivity.
Long-term stability (≥ 28 days) in chemically-defined conditions.
Efficiency
Tailored experimental designs and readouts.
In-house evaluations of experiments and results.
Rapid turnaround of results and reports.
HTS compatibility - run 3,000 to 10,000 spheroids in parallel.
Support
Extensive customer support from project initiation to closure.
Integrative analysis of results by experienced toxicologists.
Consulting for follow-up studies.
Chronic Toxicity Studies
Drug safety is the main reason for the termination of drug development programs in clinical stages and the liver is amongst the organ systems most relevant for safety failures (Cook et al., Nat Rev Drug Disc, 2014. Read…)
2D in vitro systems that are currently used to assess the hepatotoxic potential of drugs have important limitations. Hepatocytes in 2D monolayer cultures have significantly reduced functionality and metabolic capacity, which impairs their utility for prediction of drug behavior in vivo.
In contrast, the 3D spheroid system offers long term morphological and phenotypical stability for multiple weeks, and is therefore an optimal tool for long-term studies. The prolonged viability and functionality, including drastically elevated metabolic competence, enable chronic exposure studies thus facilitating drug screening for chronic DILI.
The 3D spheroid system used by HepaPredict predicts hepatotoxicity with an unmatched sensitivity using considerably lower exposure concentrations compared to other spheroid models. Our system successfully flagged 69% of hepatotoxins that caused fatal liver injuries resulting in withdrawal or black box warnings as significantly toxic at or below 20x human cmax after two weeks of exposure. With proven 100% specificity and 69% sensitivity, the HepaPredict system easily outperforms 2D cultures and other spheroid models.
Compounds implicated in clinical DILI events exhibit substantial hepatotoxicity.
Figure from Vorrink et al., Tox Sci, 2018. Read…
Fialuridine: A key example for unreliable preclinical safety assessments.
Fialuridine (FIAU), a nucleoside analogue for therapy of chronic hepatitis B infections did not show toxicity, neither in primary human hepatocyte 2D cultures nor in any animal systems tested, including mouse, rat, dog and cynomolgus monkey (McKenzie et al., NEJM, 1995. Read…).
Yet, in clinical trials, 7/15 patients developed severe hepatotoxicity, several weeks after beginning FIAU treatment, five of which died.
The 3D spheroid model successfully predicted FIAU toxicity in vitro with an EC50 of 100 nM, thus indicating that the spheroid system can provide a powerful tool to predict compound toxicity during pre-clinical drug development stages, which are not detected in commonly used in vitro or animal systems.
The 3D spheroid system detects hepatotoxicity that only manifest after prolonged exposure.
Figure from Bell et al., SciRep, 2016. Read…
Short-term exposures - Quick toxicity screenings to identify the most toxic drugs.
Long-term exposures - Repeated dose toxicity screenings for best DILI prediction.
Hepatocytes of different species: human, mouse, rat, minipig, dog, or monkey.
Compare DILI predictions in monocultures vs. cocultures with various NPCs.
What we offer
Long-term Metabolic Analyses
Prolonged viability and functionality, including the expression and function of drug metabolizing enzymes, are essential to accurately predict hepatotoxicity for chronic DILI in vitro.
The 3D spheroid system used by HepaPredict has been extensively assessed for functional stability. Primary human hepatocytes in this system retain expression of phase 1 and phase 2 drug metabolizing enzymes and drug transporters for multiple weeks in culture.
Hepatic expression signatures are preserved for multiple weeks in in 3D spheroid culture.
Inter-individual differences in metabolic patterns are preserved in 3D spheroid culture.
Figures from Vorrink et al., FASEB J, 2017. Read…
As a consequence, metabolic patterns remain temporally stable, as demonstrated by maintained metabolic profiles of dextromethorphan.
Moreover, when comparing hepatocytes from donors which classified phenotypically as extensive (EM) or poor (PM) CYP2D6 metabolizers, clear differences in dextromethorphan metabolism could be observed.
Thus, metabolic profiles are not only stable in 3D spheroid culture but also reflect phenotypic differences observed in vivo. This constitutes a key prerequisite for metabolic profiling, pharmacokinetic analyses and drug clearance assessments – all of which we provide to our clients.
Metabolic profiling
Pharmacokinetic analyses
Drug clearance assessments
Identification of enzymes responsible for drug metabolism
What we offer
Enzyme Induction Studies
Induction of drug metabolizing enzymes (DMEs) constitutes a serious concern during drug development, as it can impact the efficacy and safety of drug candidates mostly but not exclusively when co-administered with other medications.
Induction of cytochrome P450 (CYP) 3A4 is an important cause of drug–drug interactions. Therefore, drug candidates with CYP3A4 induction liability should be identified as early as possible during drug development.
PHH 3D spheroids detect in vivo CYP3A4 inducers at clinically relevant concentrations.
Figure from Hendriks et al., CPT, 2020. Read…
The 3D spheroid system used by HepaPredict can be used as a CYP3A4 induction screening model. It has proven 100% sensitivity and 100% specificity when screening 25 drugs (12 known CYP3A4 inducers in vivo and 13 negative controls) at physiologically relevant concentrations.
Induction of DMEs occurs primarily by transcriptional stimulation mediated by nuclear receptors (NRs), such as PXR and CAR, and thus relies on sufficient NR levels.
Importantly, expression of NRs is rapidly downregulated in conventional 2D culture models, whereas they remain constant in the 3D spheroid system over multiple weeks.
Expression of important hepatic xenobiotic sensors is preserved for multiple weeks in 3D spheroid culture.
Figure from Vorrink et al., FASEB J, 2017. Read…
Short-term and long-term induction and inhibition studies of drug metabolizing enzymes, nuclear receptors, and other targets.
Various endpoints including viability, gene expression and immunofluorescence.
What we offer
Drug Target Validation
Developing a drug from early screening stages to regulatory approval is a cost and time consuming process that can take 12-15 years and has been estimated to cost 2.6 billion US$. Importantly, lowest success rates are seen in clinical stages of development. Thus, drug target validation is of paramount importance early in the drug-discovery process.
The 3D spheroid system used by HepaPredict enables the use of sense reversal strategies through modulation of expression of the gene(s) of interest and subsequent monitoring the effects on the efficacy of the drug candidate using a multitude of biochemical and molecular endpoints.
Thereby, we can provide proof-of-concept data that directly demonstrate whether the potential target is indeed implicated in drug action, thus bolstering confidence and reducing the likelihood of expensive failures of poorly-chosen candidates.
The importance of validated drug targets in drug discovery and development.
Figure from Bell et al., SciRep, 2016. Read…
Modulation of gene expression
Knockdown or chemical inhibition of drug targets.
Overexpression of drug targets or other genes of interest.
What we offer
Disease Models
HepaPredict offers pathophysiological model systems for a range of clinically important liver diseases.
MASLD & MASH
Background
Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), is the most common liver disease affecting between 20% and 44% of European adults and 43-70% of patients with type 2 diabetes (Blachier et al., J Hep, 2013. Read…). Onset of MASLD is hallmarked by the accumulation of lipids within hepatocytes (hepatic steatosis), which can also be induced by a variety of drugs.
Steatosis can progress into metabolic dysfunction-associated steatohepatitis (MASH), previously known as non-alcoholic steatohepatitis (NASH), an inflammatory condition that can result in liver failure, in which Kupffer cells and the pro-inflammatory cytokines they secrete are of fundamental importance.
Moreover, increased intracellular lipid levels are an important source of reactive oxygen species (ROS), which can activate stellate cells and, in turn, lead to collagen deposition and liver scarring (hepatic fibrosis) (Matsuzawa et al., Hepatology, 2007. Read…).
Previous MASLD and MASH models
The transition from steatosis to MASH, fibrosis and HCC is characterized by an intricate interplay of a multitude of nutritional and genetic factors, pathways and cell types.
Current models utilize PHH in conventional 2D cultures, which rapidly dedifferentiate and lose hepatocyte-specific functions, thus significantly limiting their utility for long-term functional studies.
Moreover, due to pronounced species differences, there is no animal model available that replicates the full spectrum of MASLD manifestations observed in humans (Takahashi et al., WJG, 2012. Read…).
The MASLD and MASH model used by HepaPredict
The 3D spheroid model used by HepaPredict is extensively characterized with regards to expression levels and activities of fatty acid uptake transporters, key transcription factors involved in lipogenesis, insulin signaling transducers as well as the lipid-metabolic enzymes on protein and transcript level (Bell et al., SciRep, 2016. Read…; Bell et al., DMD, 2017. Read…).
Importantly, PHH are susceptible to nutrient induced lipid accumulation, when exposed to elevated levels of fatty acids, fructose and insulin, as is the case in MASLD in vivo (Feaver et al., JCI Insight, 2016. Read…).
The 3D spheroid system has been optimized to support the co-culture of hepatocytes with other primary non-parenchymal cells (Bell et al., SciRep, 2016. Read…), thus allowing to mimic the delicate interactions between hepatic cell types that are a prerequisite for the progression of steatosis to MASH.
Fibrosis
Background
Liver fibrosis is a pathological condition characterized by the accumulation of extracellular matrix proteins including collagen, elastin and laminin, resulting in increased production and decreased degradation of ECM. Left untreated, fibrosis may develop into cirrhosis which can result in liver failure and death. Liver cirrhosis is currently the fourth most common cause of death in Europe.
The scientific consensus points clearly towards the reversibility of liver fibrosis, however no therapies have been approved to date and thus it is of vital importance that realistic in vitro models are available to assist in the development process.
Previous fibrosis models
Current models of liver fibrosis include monolayers of cultured rodent or human cells, which are activated via profibrotic cytokines. Such models fail to mimic the full complexity of in vivo liver tissue due to their 2D nature and the lack of other cell types included.
The fibrosis model used by HepaPredict
The 3D spheroid model used by HepaPredict incorporates both PHHs and NPCs, thus presenting an accurate portrayal of in vivo liver tissue. Given that the incorporated cells maintain their metabolic profiles for longer segments of time in comparison to 2D cultures, a disease model of liver fibrosis can be represented in the 3D spheroid system, functioning as a unique tool for anti-fibrotic drug screening.
Cholestasis
Background
Cholestatic and mixed hepatocellular/cholestatic injuries account for up to 50% of all cases of drug-induced liver injury and are thus highly relevant for drug development (Björnsson et al., Hepatology, 2005. Read…). Drug-induced cholestasis (DIC) manifests due to impaired bile acid (BA) homeostasis, which results in the intrahepatic accumulation of BAs, causing induction of apoptosis (Yang et al., Journal Pharm Sci, 2013. Read…).
DIC can result from interference of drugs or their metabolites with the function of the bile salt export pump (BSEP), which constitutes the predominant BA export transporter (Morgan et al., Toxicol Sci, 2010. Read…).
Previous cholestatic models
Preclinical prediction of DIC previously relied exclusively on assessing BSEP activity using membrane vesicles (Morgan et al., Toxicol Sci, 2010. Read…) or hepatocytes in sandwich culture (Ansede et al., Drug Metab Dispos, 2010. Read…). Yet, this confined perspective neglects other mediators of BA homeostasis that play a role in cholestatic liver injury. Furthermore, symptoms of DIC often only manifest weeks after the patients commenced treatment.
A major limitation of the currently used DIC in vitro models is the inability to maintain hepatic cells in a differentiated state, resulting in loss of expression of BA transporters and conjugating enzymes.
In sandwich culture, PHH retain functional bile canalicular networks for several days, which is of great value for studies of hepatobiliary transport and DIC. Yet, dedifferentiation in sandwich-cultured PHH is only delayed but not stalled and thus, culturing PHH for the timeframes necessary for DIC to manifest in vivo is not possible (Rowe et al., Hepatology, 2013. Read…).
The cholestasis model used by HepaPredict
In the 3D spheroid model used by HepaPredict the relevant major bile acid transporters are expressed for multiple weeks in culture (Hendriks et al., SciRep, 2016. Read…). This feature allows to faithfully identify compounds with cholestatic liability by co-exposing spheroid cultures with BAs and candidate drugs of interest.
The cholestatic model could separate cholestatic agents from compounds that have not been implicated in hepatic cholestasis with 86% sensitivity and 100% specificity.
Extensively characterized models for MASLD/MASH (NAFLD/NASH), fibrosis, and cholestasis.
Disease models are optimized to support the co-culture of hepatocytes with other primary non-parenchymal cells funtioning as a unique tool for disease mitigating drug screening.
Identification of compounds with disease inducing liability.
Simultaneous assessment of multiple disease parameters, including steatosis, fibrosis, and inflammation.