Laboratory Animal Sciences 2019

Pharmaceutical research and development efforts are often both inefficient and suffer from a high attrition rate of drug candidates within the clinical phase of development.  Most drug trials either fail to meet their expected endpoints or show minimal statistical differentiation between active and placebo (i.e. efficaciousness).  In other instances, failures might occur due to safety reasons.  Clearly, a fundamental understanding of drug properties in the discovery and early phases of development as well as an accrual of knowledge regarding mechanisms of disease and clinical trial learnings is essential to increase productivity and success for ongoing drug development efforts.

Assuming that much of prior knowledge from prior drug development and trial efforts could be aggregated within some form of data management system, it has been proposed that systematic modeling and simulation-based trial designs could enhance the odds for successful commercialization of new drug entities.  To that end, the application of micro-physiological systems (MPS) or organs-on-a-chip in drug discovery for the development of enhanced in-vitro models to simulate or predict in-vivo processes has begun to show a lot of potential.  

While the utilization of MPS-based technologies could someday reap enormous scientific and regulatory benefits for patients, certain barriers must still be overcome which are impactful to the evolution and future implementation of these technologies.  The intrinsic challenges as well as potential solutions will be discussed.
 

Learning Objectives: 

1. Learn about intrinsic challenges and potential solutions
2. Immediate outcomes of utilizing reliable in-vitro models

The lung is a highly complex organ, comprised of more than 40 cell types that are responsible for various important functions, the lung’s complexity contributes to the subsequent challenges with developing complex in vitro co-culture models (also called micro-physiological systems or (MPS) or organs-on-ships). In vivo pharmacology naturally fulfills an important role in drug discovery, enabling benchmarking and selection of lead compounds against a particular target and understanding of PK/PD relationships to enable clinical dose prediction and calculation of safety margins amongst other roles.  

Although there are a myriad of considerations and limitations in the development and qualification of such in vitro systems, MPS exhibit great promise in the fields of pharmacology and toxicology. Successful development and implementation of MPS may enable assessment of human translation of mechanistic responses observed in non-clinical species, potentially increasing the clinical relevance of efficacy or safety endpoints, while decreasing overall animal use. This article summarizes, from the pharmaceutical industry perspective, essential elements in the development and qualification of lung MPS that MPS developers and manufacturers can adapt to facilitate the rapid implementation of these models for safety evaluation during the drug development process.

Learning Objectives: 

1. What role can ex vivo models and ‘lung-on a-chip’ model play in respiratory drug discovery? 
2. A look into the future: considerations for design and utility of the next generation micro-physiological systems for respiratory drug discovery  

This presentation will discuss and review the promise and potential of 3D Microtissues, and the challenges of using these Microtissues as Hazard ID tools. Lastly, we will discuss the potential application of Neural Microtissues in drug discovery screening. 

Learning Objectives: 

1. Understanding the strengths and limitations of in vitro and in vivo assays for hazard identification and risk assessment.  
2. Examining how 3D Microtissues can improve hazard identification in drug discovery, and de-risking during drug development.  

The goal of transforming one’s pipeline to a steady source of usable data is within our reach. Data that could be used for clinical insights or earlier in the drug discovery process.  Diverse data types that requires informatics tools to be integrated and analyzed. To reach that goal, to digitize our work, initial steps are required to collect the data, curate it and store it so it can be leveraged. This presentation will describe how we used different technologies to address the specific needs in various scientific domains. Topics such as scientific data collection, software architecture, data integration will be considered.

Learning Objectives: 

1. Understand generic scientific data modeling
2. Understand software architecture
 

Experimental models that promise to replace animal tests that are currently required for drugs and chemicals are rapidly proliferating. This includes a number of novel solutions offered by biomedical engineers that are collectively known as microphysiological systems or tissue chips. These elegant models aim to recreate a tissue or a physiological function using human cells that are usually cultured in 3D structures and under media flow. However, while the advances in biomedical engineering and material science are truly encouraging, there has been a challenge of transferring these technologies from the developer labs to the end-users. One of the barriers to the technology transfer of tissue chips has been a concern that these devices are too difficult to operate as they require specialized equipment, knowledge and experience; hence, the confidence in how well tissue chips perform is yet to be established. To bridge the gap developments in tissue chips and their use for decision making in drug development and chemical safety evaluation, the National Center for Advancing Translational Sciences has funded several Centers to test tissue chips in an independent third-party environment. This presentation will detail the experiences of one such center at Texas A&M University. 

Learning Objectives: 

1. To become familiar with the diversity of current options for the Microphysiological Systems (also known as Tissue Chips)
2. To understand how these microphysiological systems may be tested with respect to reproducibility and technology transfer.

Comparative oncology is the study of naturally-occurring cancers in pet animals (mainly dogs) to broaden and deepen our collective understanding of cancers in both companion species and humans. In this presentation, you will learn about the intramural National Cancer Institute’s Comparative Oncology Program (COP) and Comparative Oncology Trials Consortium (COTC), which provide the necessary infrastructure and expertise in comparative oncology trial design and execution to support studies that are designed to advance and inform human cancer drug development. Several specific examples of how the approach has been applied to the development of novel small molecules, biologic agents, immune-oncology approaches will be presented. This presentation will illustrate how integration of comparative oncology studies can inform the process of drug development for human patients, and demonstrate the value of the approach for the drug development community/relevant stakeholders.

Learning Objectives: 

1. The audience will gain an appreciation and understanding of the value of spontaneous cancers that develop naturally in companion animals in studies of cancer biology and therapy;
2. The audience will gain an understanding of how comparative oncology clinical trials are conducted through the NCI’s Comparative Oncology Trials Consortium to address specific drug development questions, which are complementary to the conventional preclinical testing carried out in other animal models and to Phase 1-2 data collected from human patients.

As we look towards data to help generate insight and analytics across the entire drug discovery value chain, learn how interconnected data is from the various stages of preclinical, clinical, and commercial while learning how we can streamline data resources, systems and processes to best support analytics across your business. 

Learning Objectives: 

1. Best practices to streamline and aggregate processes and sources
2. Understanding how the structure of data flows between throughout drug discovery and the impacts it has 

Approximately 30% of drugs have failed in human clinical trials due to adverse reactions despite promising pre-clinical studies, and another 60% fail due to lack of efficacy. The NIH Tissue Chips program is developing alternative approaches for more reliable readouts of toxicity or efficacy during drug development. Tissue chips are bioengineered microphysiological systems utilizing chip technology and microfluidics that mimic tissue cytoarchitecture and functional units of human organs. These microfabricated devices are useful for modeling human diseases, and for studies in precision medicine and environment exposures.

Learning Objectives:

1. Overview of the NIH Tissue Chips or Microphysiological Systems program as predictive tools for safety and efficacy studies
2. Learn about diversity of various platforms being used and future initiatives using this technology
 

Preclinical drug discovery is at the edge of a major transformation that promises to improve translation to the clinic through enhanced acquisition and advanced analysis of data. While an important part of the drug development process, currently preclinical studies do not always predict drug failure or success in the clinic. Limited predictive power is attributed to many factors including limited measurable parameters on a single animal, infrequent collection, and small sample sizes that are often captured under conditions that have the potential to alter the animal’s physiologic state and confound data interpretation. Digital biomarkers, captured continuously without handling, provide objective, sensitive, and clinically meaningful methods of monitoring disease and response to therapeutic interventions. This webinar reviews the the current state of digital biomarkers in preclinical studies and discusses the challenges and opportunities for more widespread adoption to improve translation of preclinical studies to the clinic.

Learning Objectives: 

1. Define digital biomarkers and current state in drug development
2. Examine how high frequency capture of digital biomarkers provides objective, sensitive, and meaningful readouts of disease state and compound efficacy that may be more translatable to the clinic.
3. Discuss challenges and opportunities for the future capture and analysis of digital biomarkers in preclinical studies

Animal welfare is the most important issue in any in vivo laboratory. The ability to detect and intervene in cases where the conditions of animals may be deteriorating as well as the ability ensure that undue stress and anxiety are avoided is of paramount importance. Remembering that rodents, despite the fact that they are in the laboratory setting, are social creatures and respond adversely to disruption in their routines through undue handling and or disruption of circadian rhythm is important to ensuring the quality of subsequent in vivo studies in cognition, function and behaviour. It is for this reason that longitudinal monitoring of group housed animals is required. We have shown here salient examples of what occurs when animals are not being directly observed and how animal behaviour can be observed and monitored at in their home cage and at the times when they are most likely to manifest behaviours that are more than likely true to their behavioural phenotype. In addition, we show how grouped housing and minimal handling can be achieved in order to contribute to the 3R ethos as well as impact directly on the quality of the data that is generated from in vivo experiments.

Learning Objectives: 

1. How remote monitoring in the home-cage of grouped housed animal is achieved
2. How this technology can contribute to both animal welfare and the quality of in vivo studies through rapid intervention and earlier recognition of humane end-points

Xenobiotic-induced cardiotoxicity is a major concern for both pharmaceuticals and chemicals in the marketplace. For drugs, "Thorough QT/corrected QT (QTc)" (TQT) studies are cornerstones of clinical cardiovascular safety assessment. However, TQT studies are resource intensive, and preclinical models predictive of the threshold of regulatory concern are lacking. For other chemicals, cardiotoxicity is not routinely assessed, and is largely inferred from epidemiologic data.  We hypothesized that an in vitro model using induced pluripotent stem cell (iPSC)-derived cardiomyocytes from a diverse sample of human subjects can serve as a "TQT study in a dish," improving cardiotoxicity assessments for both pharmaceutically and chemicals in commerce. For 10 positive and 3 negative control drugs, in vitro concentration-QTc, computed using a population Bayesian model, accurately predicted known in vivo concentration-QTc. Moreover, predictions of the percent confidence that the regulatory threshold of 10 ms QTc prolongation would be breached were also consistent with in vivo evidence. This "TQT study in a dish," consisting of a population-based iPSC-derived cardiomyocyte model and Bayesian concentration-QTc modeling, has several advantages over existing in vitro platforms, including higher throughput, lower cost, and the ability to accurately predict the in vivo concentration range below the threshold of regulatory concern.  These results demonstrate the potential for replacing a multi-million dollar clinical trial – the Thorough QT/QTc study – with an in vitro-in silico model.  Moreover, because cardiotoxicity clinical trials are not performed for non-pharmaceuticals, such a model could fill a critical gap in chemical toxicity testing.  

Learning Objectives: 

1. Describe current practices in cardiotoxicity assessment for xenobiotics.
2. Explain how induced pluripotent stem cell-derived cardiomyocytes may be useful in advancing cardiotoxicity assessment.

A collection of opinions, questions and other assorted thoughts about the intersection of these developing technologies and preclinical studies primarily focused on the early discovery (as opposed to the safety assessment) aspects of drug discovery.

Learning Objectives:

1. How are digital technologies being used in clinical studies and clinical medicine practice?
2. What are some possible benefits of using digital technology in preclinical studies?

Digitalization has transformed virtually every industry, but it has been slow to gain traction within the preclinical phase of the drug development journey. Recent advances in digital vivarium technologies present opportunities to improve study precision, data management, monitoring and extraction from animal studies. Engaging in non-traditional models in vitro (such as organ-on-chip) and in vivo in companion animals has the potential to positively impact the preclinical phase of drug development. 

These novel models and digital technologies could enhance the reproducibility and clinical relevance of preclinical studies, increase the sensitivity for detecting pharmacologically or toxicologically significant changes, accelerate the development of novel anti-cancer therapies and even yield animal welfare benefits. These capabilities could add significant value to our current approaches to drug development animal studies. 

Learning Objectives: 

1. Overview of emerging vivarium technologies
2. Organ-on-chip systems primer
3. Introduction to the field of comparative oncology

The printing press, the automobile & the Internet are just a few technological achievements that have advanced our world. All were driven by human ingenuity: our innate creativity that inspires us to learn, imagine & explore.
This spirit is what pushes us to challenge the boundaries of the possible to go ever forward.
 
Today, AI is helping to amplify our human ingenuity, opening up exciting new possibilities for how intelligent technology can shape our world. At Microsoft, our goal is to democratize access to AI for everyone through innovative & powerful platforms, & above all, we’re focused on ensuring that our AI tools & technologies are deployed responsibly & earn people’s trust. 
 
And yet, we realize that AI is one of the lesser understood modern technological break-throughs. Many questions remain. How are companies applying this technology to empower employees, engage with customers, transform their business and optimize their operations? Where are they seeing benefits, and what are their blockers?

Learning Objectives: 

1. What is AI and what's the impact on business
2. What are the opportunities to embracing AI in life science