FuSe: a tool to move RNA-Seq analyses from chromosomal/gene loci to functional grouping of mRNA transcripts.

SUMMARY: Typical RNA sequencing (RNA-Seq) analyses are performed either at the gene level by summing all reads from the same locus, assuming that all transcripts from a gene make a protein or at the transcript level, assuming that each transcript displays unique function. However, these assumptions are flawed, as a gene can code for different types of transcripts and different transcripts are capable of synthesizing similar, different or no protein. As a consequence, functional changes are not well illustrated by either gene or transcript analyses. We propose to improve RNA-Seq analyses by grouping the transcripts based on their similar functions. We developed FuSe to predict functional similarities using the primary and secondary structure of proteins. To estimate the likelihood of proteins with similar functions, FuSe computes two confidence scores: knowledge (KS) and discovery (DS) for protein pairs. Overlapping protein pairs exhibiting high confidence are grouped to form 'similar function protein groups' and expression is calculated for each functional group. The impact of using FuSe is demonstrated on in vitro cells exposed to paracetamol, which highlight genes responsible for cell adhesion and glycogen regulation which were earlier shown to be not differentially expressed with traditional analysis methods. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/rajinder4489/FuSe. Data for APAP exposure are available in the BioStudies database (http://www.ebi.ac.uk/biostudies) under accession numbers S-HECA143, S-HECA(158) and S-HECA139. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Translational precision medicine: an industry perspective.

In the era of precision medicine, digital technologies and artificial intelligence, drug discovery and development face unprecedented opportunities for product and business model innovation, fundamentally changing the traditional approach of how drugs are discovered, developed and marketed. Critical to this transformation is the adoption of new technologies in the drug development process, catalyzing the transition from serendipity-driven to data-driven medicine. This paradigm shift comes with a need for both translation and precision, leading to a modern Translational Precision Medicine approach to drug discovery and development. Key components of Translational Precision Medicine are multi-omics profiling, digital biomarkers, model-based data integration, artificial intelligence, biomarker-guided trial designs and patient-centric companion diagnostics. In this review, we summarize and critically discuss the potential and challenges of Translational Precision Medicine from a cross-industry perspective.

Snapshot 3D reconstruction of liquid surfaces.

In contrast to static objects, liquid structures such as drops, blobs, as well as waves and ripples on water surfaces are challenging to image in 3D due to two main reasons: first, the transient nature of those phenomena requires snapshot imaging that is fast enough to freeze the motion of the liquid. Second, the transparency of liquids and the specular reflections from their surfaces induce complex image artefacts. In this article we present a novel imaging approach to reconstruct in 3D the surface of irregular liquid structures that only requires a single snapshot. The technique is named Fringe Projection - Laser Induced Fluorescence (FP-LIF) and uses a high concentration of fluorescent dye in the probed liquid. By exciting this dye with a fringe projection structured laser beam, fluorescence is generated primarily at the liquid surface and imaged at a backward angle. By analysing the deformation of the initial projected fringes using phase-demodulation image post-processing, the 3D coordinates of the liquid surface are deduced. In this article, the approach is first numerically tested by considering a simulated pending drop, in order to analyse its performance. Then, FP-LIF is applied for two experimental cases: a quasi-static pending drop as well as a transient liquid sheet. We demonstrate reconstruction RMS errors of 1.4% and 6.1% for the simulated and experimental cases respectively. The technique presented here demonstrates, for the first time, a fringe projection approach based on LIF detection to reconstruct liquid surfaces in 3D. FP-LIF is promising for the study of more complex liquid structures and is paving the way for high-speed 3D videography of liquid surfaces.

Are Biotransformation Studies of Therapeutic Proteins Needed? Scientific Considerations and Technical Challenges.

For therapeutic proteins, the currently established standard development path generally does not foresee biotransformation studies by default because it is well known that the clearance of therapeutic proteins proceeds via degradation to small peptides and individual amino acids. In contrast to small molecules, there is no general need to identify enzymes involved in biotransformation because this information is not relevant for drug-drug interaction assessment and for understanding the clearance of a therapeutic protein. Nevertheless, there are good reasons to embark on biotransformation studies, especially for complex therapeutic proteins. Typical triggers are unexpected rapid clearance, species differences in clearance not following the typical allometric relationship, a mismatch in the pharmacokinetics/pharmacodynamics (PK/PD) relationship, and the need to understand observed differences between the results of multiple bioanalytical methods (e.g., total vs. target-binding competent antibody concentrations). Early on during compound optimization, knowledge on protein biotransformation may help to design more stable drug candidates with favorable in vivo PK properties. Understanding the biotransformation of a therapeutic protein may also support designing and understanding the bioanalytical assay and ultimately the PK/PD assessment. Especially in cases where biotransformation products are pharmacologically active, quantification and assessment of their contribution to the overall pharmacological effect can be important for establishing a PK/PD relationship and extrapolation to humans. With the increasing number of complex therapeutic protein formats, the need for understanding the biotransformation of therapeutic proteins becomes more urgent. This article provides an overview on biotransformation processes, proteases involved, strategic considerations, regulatory guidelines, literature examples for in vitro and in vivo biotransformation, and technical approaches to study protein biotransformation. SIGNIFICANCE STATEMENT: Understanding the biotransformation of complex therapeutic proteins can be crucial for establishing a pharmacokinetic/pharmacodynamic relationship. This article will highlight scientific, strategic, regulatory, and technological features of protein biotransformation.

Current limitations and future opportunities for prediction of DILI from in vitro.

Drug-induced liver injury (DILI) is a major concern for drug developers, regulators and clinicians. It is triggered by drug and xenobiotic insults leading to liver impairment or damage, in the worst-case liver failure. In contrast to acute "intrinsic" hepatotoxicity, DILI typically manifests in a very small subset of the population under treatment with no clear dose relationship and inconsistent temporal patterns and is therefore termed an idiosyncratic event. Involved are multifactorial, compound-dependent mechanisms and host-specific factors, making the prediction in preclinical test systems very challenging. While preclinical safety studies in animals usually are able to capture direct, acute liver toxicities, they are less predictive for human DILI, where specific, human-derived in vitro models can potentially close the gap. On one hand, mechanistic approaches addressing key mechanisms involved in DILI in well-characterized and standardized in vitro test systems have been developed. On the other hand, co-cultures of different cell types, including patient- and/or stem cell-derived cells, in a three-dimensional setup allow for prolonged incubations and multiplexed readouts. Such complex setups might better reflect multifactorial human DILI. One major challenge is that for many compounds with human DILI the underlying mechanisms are not yet fully understood, complicating establishment and validation of predictive cellular tools. A tiered approach including rapid mechanism-based in vitro screens followed by confirmatory tests in more physiologically relevant models might allow minimizing DILI risk early on in vitro. Such complex, integrated approaches will gain from larger collaborations in multidisciplinary groups bringing existing knowledge and state-of-the-art technology together.

Temporal Patterns of Novel Circulating Biomarkers in IL-2-mediated Vascular Injury in the Rat.

Recombinant interleukin-2 (rIL-2) administration in oncology indications is hampered by vascular toxicity, which presents as a vascular leak syndrome. We used this aspect of the toxicity of rIL-2 to evaluate candidate biomarkers of drug-induced vascular injury (DIVI) in rats given 0.36 mg/kg rIL-2 daily. Groups of rats were given either 2 or 5 doses of rIL-2 or 5 doses of rIL-2 followed by a 7-day recovery. The histomorphologic lexicon and grading scheme developed by the Vascular Injury Working Group of the Predictive Safety Testing Consortium of the Critical Path Institute were utilized to enable semiquantitative integration with circulating biomarker levels. The administration of rIL-2 was associated with time-dependent endothelial cell hyperplasia and hypertrophy and perivascular inflammation that correlated with increases in circulating angiopoietin-2, lipocalin-2, monocyte chemotactic protein-1, tissue inhibitor of metalloproteinase-1, vascular endothelial growth factor A, E-selectin, and chemokine (C-X-C motif) ligand-1, and the microRNAs miR-21, miR-132, and miR-155. The dose groups were differentially identified by panels comprising novel candidate biomarkers and traditional hematologic parameters. These results identify biomarkers of the early stages of DIVI prior to the onset of vascular smooth muscle necrosis.

Model-based assessment of erlotinib effect in vitro measured by real-time cell analysis.

Real time cell analysis (RTCA) is an impedance-based technology which tracks various living cell characteristics over time, such as their number, morphology or adhesion to the extra cellular matrix. However, there is no consensus about how RTCA data should be used to quantitatively evaluate pharmacodynamic parameters which describe drug efficacy or toxicity. The purpose of this work was to determine how RTCA data can be analyzed with mathematical modeling to explore and quantify drug effect in vitro. The pharmacokinetic-pharmacodynamic erlotinib concentration profile predicted by the model and its effect on the human epidermoïd carcinoma cell line A431 in vitro was measured through RTCA output, designated as cell index. A population approach was used to estimate model parameter values, considering a plate well as the statistical unit. The model related the cell index to the number of cells by means of a proportionality factor. Cell growth was described by an exponential model. A delay between erlotinib pharmacokinetics and cell killing was described by a transit compartment model, and the effect potency, by an E max function of erlotinib concentration. The modeling analysis performed on RTCA data distinguished drug effects in vitro on cell number from other effects likely to modify the relationship between cell index and cell number. It also revealed a time-dependent decrease of erlotinib concentration over time, described by a mono-exponential pharmacokinetic model with nonspecific binding.

Taking the leap toward human-specific nonanimal methodologies: The need for harmonizing global policies for microphysiological systems.

With a recent amendment, India joined other countries that have removed the legislative barrier toward the use of human-relevant methods in drug development. Here, global stakeholders weigh in on the urgent need to globally harmonize the guidelines toward the standardization of microphysiological systems. We discuss a possible framework for establishing scientific confidence and regulatory approval of these methods.

A long-term three dimensional liver co-culture system for improved prediction of clinically relevant drug-induced hepatotoxicity.

Drug-induced liver injury (DILI) is the major cause for liver failure and post-marketing drug withdrawals. Due to species-specific differences in hepatocellular function, animal experiments to assess potential liabilities of drug candidates can predict hepatotoxicity in humans only to a certain extent. In addition to animal experimentation, primary hepatocytes from rat or human are widely used for pre-clinical safety assessment. However, as many toxic responses in vivo are mediated by a complex interplay among different cell types and often require chronic drug exposures, the predictive performance of hepatocytes is very limited. Here, we established and characterized human and rat in vitro three-dimensional (3D) liver co-culture systems containing primary parenchymal and non-parenchymal hepatic cells. Our data demonstrate that cells cultured on a 3D scaffold have a preserved composition of hepatocytes, stellate, Kupffer and endothelial cells and maintain liver function for up to 3months, as measured by the production of albumin, fibrinogen, transferrin and urea. Additionally, 3D liver co-cultures maintain cytochrome P450 inducibility, form bile canaliculi-like structures and respond to inflammatory stimuli. Upon incubation with selected hepatotoxicants including drugs which have been shown to induce idiosyncratic toxicity, we demonstrated that this model better detected in vivo drug-induced toxicity, including species-specific drug effects, when compared to monolayer hepatocyte cultures. In conclusion, our results underline the importance of more complex and long lasting in vitro cell culture models that contain all liver cell types and allow repeated drug-treatments for detection of in vivo-relevant adverse drug effects.

The evolving role of investigative toxicology in the pharmaceutical industry.

For decades, preclinical toxicology was essentially a descriptive discipline in which treatment-related effects were carefully reported and used as a basis to calculate safety margins for drug candidates. In recent years, however, technological advances have increasingly enabled researchers to gain insights into toxicity mechanisms, supporting greater understanding of species relevance and translatability to humans, prediction of safety events, mitigation of side effects and development of safety biomarkers. Consequently, investigative (or mechanistic) toxicology has been gaining momentum and is now a key capability in the pharmaceutical industry. Here, we provide an overview of the current status of the field using case studies and discuss the potential impact of ongoing technological developments, based on a survey of investigative toxicologists from 14 European-based medium-sized to large pharmaceutical companies.

New approach methodologies in human regulatory toxicology - Not if, but how and when!

The predominantly animal-centric approach of chemical safety assessment has increasingly come under pressure. Society is questioning overall performance, sustainability, continued relevance for human health risk assessment and ethics of this system, demanding a change of paradigm. At the same time, the scientific toolbox used for risk assessment is continuously enriched by the development of "New Approach Methodologies" (NAMs). While this term does not define the age or the state of readiness of the innovation, it covers a wide range of methods, including quantitative structure-activity relationship (QSAR) predictions, high-throughput screening (HTS) bioassays, omics applications, cell cultures, organoids, microphysiological systems (MPS), machine learning models and artificial intelligence (AI). In addition to promising faster and more efficient toxicity testing, NAMs have the potential to fundamentally transform today's regulatory work by allowing more human-relevant decision-making in terms of both hazard and exposure assessment. Yet, several obstacles hamper a broader application of NAMs in current regulatory risk assessment. Constraints in addressing repeated-dose toxicity, with particular reference to the chronic toxicity, and hesitance from relevant stakeholders, are major challenges for the implementation of NAMs in a broader context. Moreover, issues regarding predictivity, reproducibility and quantification need to be addressed and regulatory and legislative frameworks need to be adapted to NAMs. The conceptual perspective presented here has its focus on hazard assessment and is grounded on the main findings and conclusions from a symposium and workshop held in Berlin in November 2021. It intends to provide further insights into how NAMs can be gradually integrated into chemical risk assessment aimed at protection of human health, until eventually the current paradigm is replaced by an animal-free "Next Generation Risk Assessment" (NGRA).

High-speed videography of transparent media using illumination-based multiplexed schlieren.

Schlieren photography is widely used for visualizing phenomena within transparent media. The technique, which comes in a variety of configurations, is based on detecting or extracting the degree to which light is deflected whilst propagating through a sample. To date, high-speed schlieren videography can only be achieved using high-speed cameras, thus limiting the frame rate of such configurations to the capabilities of the camera. Here we demonstrate, for the first time, optically multiplexed schlieren videography, a concept that allows such hardware limitations to be bypassed, opening up for, in principle, an unlimited frame rate. By illuminating the sample with a rapid burst of uniquely spatially modulated light pulses, a temporally resolved sequence can be captured in a single photograph. The refractive index variations are thereafter measured by quantifying the local phase shift of the superimposed intensity modulations. The presented results demonstrate the ability to acquire a series of images of flame structures at frame rates up to 1 Mfps using a standard 50 fps sCMOS camera.

Gene expression-based in vivo and in vitro prediction of liver toxicity allows compound selection at an early stage of drug development.

We have analyzed gene expression and histopathology of rat liver treated with a histamine-3 receptor inverse agonist under development for the treatment of obesity 24 h after a single acute administration. While histopathology did not identify a clear liver toxicity, analysis of gene changes strongly suggested the development of toxicity. This prediction was confirmed in a 2-week repeat-dose rat study where prominent liver pathology occurred, while gene changes that lead to the prediction persisted. A subset of these genes was analyzed in vitro in both rat and human hepatocytes to reveal the potential relevancy of the findings for the situation in humans. This comprehensive analysis of the development compound at the gene expression level allowed interpretation of findings of the follow-up compound in a frontloaded 24-h single-dose acute study that was initiated before regular 2-week repeat-dose studies started. The high similarity of the follow-up compound to the lead compound based on gene expression lead to the immediate termination of the development program for this compound series. Our data demonstrate the value of genomics-based early toxicity prediction in short-term in vivo studies for the characterization of compounds to allow prioritization and selection of suited candidates before compound-, animal-, and cost-intensive longer term studies are undertaken.

Human microphysiological systems for drug development.

Organs-on-chips could be used to assess drug efficacy and support personalized medicine.

Challenging the pipeline.

This commentary presents a thought experiment seeking to answer the key question: "If you were to put aside all the traditional drug discovery processes and start a new drug discovery program that places the highest priority on human and disease-relevant models throughout the entire process, how could it be done?"

A Model-Based Workflow to Benchmark the Clinical Cholestasis Risk of Drugs.

We present a generic workflow combining physiology-based computational modeling and in vitro data to assess the clinical cholestatic risk of different drugs systematically. Changes in expression levels of genes involved in the enterohepatic circulation of bile acids were obtained from an in vitro assay mimicking 14 days of repeated drug administration for 10 marketed drugs. These changes in gene expression over time were contextualized in a physiology-based bile acid model of glycochenodeoxycholic acid. The simulated drug-induced response in bile acid concentrations was then scaled with the applied drug doses to calculate the cholestatic potential for each compound. A ranking of the cholestatic potential correlated very well with the clinical cholestasis risk obtained from medical literature. The proposed workflow allows benchmarking the cholestatic risk of novel drug candidates. We expect the application of our workflow to significantly contribute to the stratification of the cholestatic potential of new drugs and to support animal-free testing in future drug development.

Implementation of a Human Renal Proximal Tubule on a Chip for Nephrotoxicity and Drug Interaction Studies.

Proximal tubule epithelial cells (PTEC) are susceptible to drug-induced kidney injury (DIKI). Cell-based, two-dimensional (2D) in vitro PTEC models are often poor predictors of DIKI, probably due to the lack of physiological architecture and flow. Here, we assessed a high throughput, 3D microfluidic platform (Nephroscreen) for the detection of DIKI in pharmaceutical development. This system was established with four model nephrotoxic drugs (cisplatin, tenofovir, tobramycin and cyclosporin A) and tested with eight pharmaceutical compounds. Measured parameters included cell viability, release of lactate dehydrogenase (LDH) and N-acetyl-ß-d-glucosaminidase (NAG), barrier integrity, release of specific miRNAs, and gene expression of toxicity markers. Drug-transporter interactions for P-gp and MRP2/4 were also determined. The most predictive read outs for DIKI were a combination of cell viability, LDH and miRNA release. In conclusion, Nephroscreen detected DIKI in a robust manner, is compatible with automated pipetting, proved to be amenable to long-term experiments, and was easily transferred between laboratories. This proof-of-concept-study demonstrated the usability and reproducibility of Nephroscreen for the detection of DIKI and drug-transporter interactions. Nephroscreen it represents a valuable tool towards replacing animal testing and supporting the 3Rs (Reduce, Refine and Replace animal experimentation).

Human immunocompetent Organ-on-Chip platforms allow safety profiling of tumor-targeted T-cell bispecific antibodies.

Traditional drug safety assessment often fails to predict complications in humans, especially when the drug targets the immune system. Here, we show the unprecedented capability of two human Organs-on-Chips to evaluate the safety profile of T-cell bispecific antibodies (TCBs) targeting tumor antigens. Although promising for cancer immunotherapy, TCBs are associated with an on-target, off-tumor risk due to low levels of expression of tumor antigens in healthy tissues. We leveraged in vivo target expression and toxicity data of TCBs targeting folate receptor 1 (FOLR1) or carcinoembryonic antigen (CEA) to design and validate human immunocompetent Organs-on-Chips safety platforms. We discovered that the Lung-Chip and Intestine-Chip could reproduce and predict target-dependent TCB safety liabilities, based on sensitivity to key determinants thereof, such as target expression and antibody affinity. These novel tools broaden the research options available for mechanistic understandings of engineered therapeutic antibodies and assessing safety in tissues susceptible to adverse events.

Characterization of a long-term mouse primary liver 3D tissue model recapitulating innate-immune responses and drug-induced liver toxicity.

Three-dimensional liver in vitro systems have recently attracted a lot of attention in drug development. These systems help to gain unprecedented insights into drug-induced liver injury (DILI), as they more closely reproduce liver biology, and as drug effects can be studied in isolated and controllable microenvironments. Many groups established human-based in vitro models but so far neglected the animal equivalent, although the availability of both models would be desirable. Animal in vitro models enable back- and forward translation of in vitro and in vivo findings, bridge the gap between rodent in vivo and human in vitro scenarios, and ultimately support the interpretation of data generated with preclinical species and humans. Since mice are often used in drug development and physiologically relevant in vitro systems are lacking, we established, for the first time, a mouse liver model that encompasses primary parenchymal and non-parenchymal cells with preserved viability and functionality over three weeks. Using our three-dimensional liver spheroids, we were able to predict the toxicity of known DILI compounds, demonstrated the interaction cascades between the different cell types and showed evidence of drug-induced steatosis and cholestasis. In summary, our mouse liver spheroids represent a valuable in vitro model that can be applied to study DILI findings, reported from mouse studies, and offers the potential to detect immune-mediated drug-induced liver toxicity.