Human Cell Systems Biology for Drug Discovery and Chemical Safety. Presentation at the 7th Brazilian Symposium on Medicinal Chemistry, November 12, 2014, Campos do Jordao-SP, Brazil. Ellen Berg.
BioMAP® Systems for Investigative Toxicology & Safety Assessment. Presentation for the California Environmental Protection Agency’s 21st Century Toxicology Seminar Series, October 29, 2014, Sacramento, CA. Ellen Berg
A Chemical Biology Approach Using Primary Human Cell Systems and Co-Cultures for Understanding Target Biology. Presentation at SLAS 2015 4th Annual Conference, February 11, 2015, Washington DC. Ellen Berg.
Identify Compounds that Rescue Disease Relevant Mutant Membrane ProteinsDiscoverX Corporation
Learn about diseases caused by protein misfolding and how you can screen for compounds, known as pharmacochaperones, that rescue misfolded proteins and could be used as therapeutics.
Historically, genetic toxicology has been comprised of bacterial and cell based in vitro assays such as the Ames assay (a bacterial mutagenicity assay), Micronucleus and Chromosomal Aberration assays (mammalian cytogenetic assays), and Mouse Lymphoma Assay (in vitro mammalian cell gene mutation assay). These were routinely used for safety evaluation and are still part of the standard core battery. The emergence of new technologies has facilitated the development of in vitro methods for safe and effective drug and chemical testing.
This BioReliance® toxicology services webinar will explore alternative models, including 3D skin models that comply with the EC Scientific Committee on Consumer Safety (SCCS) recommendations. It will also discuss how the 3Rs (Replace, Reduce, Refine) Principle advocates the exploration of such alternative methods while achieving required goals.
In this webinar, you will learn:
• About in vitro alternatives to animal toxicity testing in pharma, chemical, tobacco, and personal care products.
• How the 3Rs (Replace, Reduce, Refine) Principle advocates exploring alternative methods without compromising the required goals.
• Alternatives to comply with the 7th Amendment to the EC Cosmetics Directive.
Answer four fundamental questions on how to develop the most innovative cancer immunotherapy treatments, starting with screening for lead molecules and ending with evaluation of combination therapies.
Introduction to Screening Models Of Anti Cancer Drugs
Need for novel anti cancer drugs, In - vitro methods, In - vivo methods, Advantages and disadvantages
Presented by
T. Niranjan Reddy
Department of Pharmacology
BioMAP® Systems for Investigative Toxicology & Safety Assessment. Presentation for the California Environmental Protection Agency’s 21st Century Toxicology Seminar Series, October 29, 2014, Sacramento, CA. Ellen Berg
A Chemical Biology Approach Using Primary Human Cell Systems and Co-Cultures for Understanding Target Biology. Presentation at SLAS 2015 4th Annual Conference, February 11, 2015, Washington DC. Ellen Berg.
Identify Compounds that Rescue Disease Relevant Mutant Membrane ProteinsDiscoverX Corporation
Learn about diseases caused by protein misfolding and how you can screen for compounds, known as pharmacochaperones, that rescue misfolded proteins and could be used as therapeutics.
Historically, genetic toxicology has been comprised of bacterial and cell based in vitro assays such as the Ames assay (a bacterial mutagenicity assay), Micronucleus and Chromosomal Aberration assays (mammalian cytogenetic assays), and Mouse Lymphoma Assay (in vitro mammalian cell gene mutation assay). These were routinely used for safety evaluation and are still part of the standard core battery. The emergence of new technologies has facilitated the development of in vitro methods for safe and effective drug and chemical testing.
This BioReliance® toxicology services webinar will explore alternative models, including 3D skin models that comply with the EC Scientific Committee on Consumer Safety (SCCS) recommendations. It will also discuss how the 3Rs (Replace, Reduce, Refine) Principle advocates the exploration of such alternative methods while achieving required goals.
In this webinar, you will learn:
• About in vitro alternatives to animal toxicity testing in pharma, chemical, tobacco, and personal care products.
• How the 3Rs (Replace, Reduce, Refine) Principle advocates exploring alternative methods without compromising the required goals.
• Alternatives to comply with the 7th Amendment to the EC Cosmetics Directive.
Answer four fundamental questions on how to develop the most innovative cancer immunotherapy treatments, starting with screening for lead molecules and ending with evaluation of combination therapies.
Introduction to Screening Models Of Anti Cancer Drugs
Need for novel anti cancer drugs, In - vitro methods, In - vivo methods, Advantages and disadvantages
Presented by
T. Niranjan Reddy
Department of Pharmacology
Learn about novel cell-based assays that enable improved immunotherapy drug development. See case studies utilizing checkpoint receptors such as PD-1, VISTA, and NIK.
Discover solutions for all phases of product development for genetox assessment from in silico analysis, screening, mode of action assessment, or GLP regulatory required assays. Our BioReliance® Genetic Toxicology Services director will share specifics and rationale for each assay category.
In this webinar you will:
- Learn the required regulatory assays
- Understand why each assay is used and how to employ different assay designs
- Learn different assays and techniques to screen potential compounds and understand mechanism and mode of action
Presented by Rohan Kulkarni, Ph.D., ERT, Director Toxicology, Study Management on February 9, 2017
The Presence and Persistence of Resistant and Stem Cell-Like Tumor Cells as a...QIAGEN
Epithelial ovarian cancer is the fifth leading cause of cancer-related deaths of women in the United States and Europe and ranks as the second most common type of gynecological malignancy. Most cases are diagnosed in advanced stages and although the response rates to platinum-based chemotherapy are high, the majority of patients nevertheless have poor survival rates. Although the reasons for these poor outcomes are likely to be multifactorial, one particular area of interest has recently focused on hematogenous tumor cell dissemination that has been shown to originate from disseminated tumor cells (DTCs) in the bone marrow (BM) and circulating tumor cells (CTCs) in the blood. Here, we demonstrate that the negative prognostic impact of CTCs and DTCs arise from specific cellular phenotypes and are associated with platinum-resistance and stem cell-associated proteins.
Learn about novel cell-based assays that enable improved immunotherapy drug development. See case studies utilizing checkpoint receptors such as PD-1, VISTA, and NIK.
Discover solutions for all phases of product development for genetox assessment from in silico analysis, screening, mode of action assessment, or GLP regulatory required assays. Our BioReliance® Genetic Toxicology Services director will share specifics and rationale for each assay category.
In this webinar you will:
- Learn the required regulatory assays
- Understand why each assay is used and how to employ different assay designs
- Learn different assays and techniques to screen potential compounds and understand mechanism and mode of action
Presented by Rohan Kulkarni, Ph.D., ERT, Director Toxicology, Study Management on February 9, 2017
The Presence and Persistence of Resistant and Stem Cell-Like Tumor Cells as a...QIAGEN
Epithelial ovarian cancer is the fifth leading cause of cancer-related deaths of women in the United States and Europe and ranks as the second most common type of gynecological malignancy. Most cases are diagnosed in advanced stages and although the response rates to platinum-based chemotherapy are high, the majority of patients nevertheless have poor survival rates. Although the reasons for these poor outcomes are likely to be multifactorial, one particular area of interest has recently focused on hematogenous tumor cell dissemination that has been shown to originate from disseminated tumor cells (DTCs) in the bone marrow (BM) and circulating tumor cells (CTCs) in the blood. Here, we demonstrate that the negative prognostic impact of CTCs and DTCs arise from specific cellular phenotypes and are associated with platinum-resistance and stem cell-associated proteins.
Leap Program is a Global Community Development Program provides opportunities for young people to create direct positive impact through an international volunteer experience abroad.
Trade Spend tops the budget for most CPG Companies and most of them are making big mistakes! Learn what tops the list of Trade Spend Mistakes you want to avoid.
Meet the possible future of Web: web components. 4 parts of web components can be used separately or together and allow us create reusable modules which we call "widgets".
2014 11-27 ODDP 2014 course, Amsterdam, Alain van GoolAlain van Gool
Presentation as part of a comprehensive oncology drug development course, to discuss a pharmaceutical approach to identify, validate and develop biomarkers for personalized medicine for melanoma.
Dr. Forsythe The Immune Protocol™ & The Lite LDIPT Protocol ™ updated 2/2/17Tahoe eLab
This presentation has been peer-reviewed for fair and balanced evidence-based medicine.
Status of FDA devices used for the material being presented: NA/Non-Clinical
Status of off-label use of devices, drugs or other materials that constitute the subject of this presentation: Discuss off-label use of chemotherapy drugs for different cancers.
Big Data and Genomic Medicine by Corey NislowKnome_Inc
View the webinar at: http://www.knome.com/webinar-big-data-genomic-medicine. This presentation covers an overview of genomic medicine, requirements and challenges of next-generation sequencing, bottlenecks to broader healthcare adoption, and why “we want to sequence everyone.”
2015 11-26 ODDP2015 Course Oncology Drug Development, Amsterdam, Alain van GoolAlain van Gool
Tutorial lecture explaining real case stories of oncology drug development, passing on lessons learned from my pharma days to an audience of research professionals.
Preclinical ToxPathology is often considered as an hidden scientific field in Pathology and it offers a lot of complexity. When implementing Digital Pathology strategies within translational workflows it is crucial to understand the basics of ToxPathology.
So, let's start with the introduction !
Assessing gastrointestinal toxicity using human tissues bioptaBiopta Inc.
Many drugs adversely affect the gastrointestinal system. This presentation describes the use of ethically-donated human tissue samples in the prediction of drug-induced gastrointestinal toxicity and will be of interest to scientists involved in drug discovery and development.
The Forsythe Immune Protocol, outcome based InvestigationTahoe eLab
Top Ten Take Home Points:
Integrative cancer medicine combines conventional and alternative treatments
Hope in victory over cancer with integrative cancer therapies
Genomic Testing (CST) on whole blood isolates circulating tumor blood cells
Genomic testing offers a blue print for individual’s cancer treatments
Genomic testing defines top chemo agents most effective in the treatment of one’s cancer
Genomic testing isolates supplements, herbs and vitamins that are most effective in the treatment of one’s cancer
Insulin Potentiated Therapy (IPT) uses insulin as its target agent
CST + IPT + Lipoic –Acid-Palladium (LAPd) Compound produces higher survivorship rates
Forsythe Immune Protocol™
shows overall survivorship rate of 70% over a 96 month period in 1400 Stage
IV cancer patients
10. Freedom to choose alternative cancer treatments is your right
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
1. Human Cell Systems for Drug Discovery
and Chemical Safety
Ellen L. Berg, Scientific Director
The 7th Brazilian Symposium on Medicinal Chemistry
Campos do Jordão-SP, Brazil, November 9-12, 2014
2. Agenda
• Challenges in pharmaceutical research
• Primary human cell systems – BioMAP
platform
• Case studies
- Understanding ADRs - thrombosis-related side
effects
- Drug combinations
2
3. • Problem:
- Pharmaceutical productivity is at an all time low
- We are swimming in oceans of data
• A need for new approaches
- Better physiological relevance
- More predictive of clinical effects
Challenges in Drug Discovery
We need to do something different: A Turning Point
3
4. Complexity of Biology
Scale (meters)
molecules pathways cells tissues humans
10-9 M 10-8 M 10-7 M 10-6 M 10-5 M 10-4 M 10-3 M 10-2 M 10-1 M 1 M
Human exposureMolecular targets
4
• Human biology is complex
- Modular, redundant, highly networked, & full of feedback loops
5. Complexity of Biology
Scale (meters)
molecules pathways cells tissues humans
10-9 M 10-8 M 10-7 M 10-6 M 10-5 M 10-4 M 10-3 M 10-2 M 10-1 M 1 M
Human exposureMolecular targets
5
• Human biology is complex
- Modular, redundant, highly networked, & full of feedback loops
• Prediction (and understanding!) is difficult
- Emergent properties
Primary human cell systems
6. Solution: Primary Human Cell Systems
• BioMAP® Profiling:
- In Vitro testing in primary human cell based tissue and
disease models
• Data driven chemical biology approach
- Data-driven research methodology
- Leverages the analysis of a large chemical biology dataset
• Applications in drug discovery
- Compound characterization across a broad range of biology
- Drug mechanisms of action – anchored on clinical outcomes
- Guidance for translational studies, indications & biomarkers
Confidential6
9. Data Driven Research
Issues
Many hypotheses are generated
Each hypothesis requires validation
Validation requires both computational
and “domain” expertise
Solution
Incorporate “domain” expertise upfront
10. BioMAP® Technology Platform
BioMAP®
Assay Systems
Reference
Profile Database
Predictive
Informatics Tools
Human primary cells
Disease-models
30+ systems
Biomarker responses to drugs
are stored in the database
>3000 drugs
Custom informatics tools are
used to predict clinical outcomes
High Throughput Human Biology
10
11. BioMAP® Systems – Key Features
11
Primary human cell types
Physiologically relevant “context”
Complex activation settings
Co-cultures
Translational biomarker endpoints
12. Feature Mice Man
Lifespan 2 Years 70 Years
Size 60 g 60 kg
Environment
Animal facility,
cage-mates
Outside world, people,
animals, etc.
Why Human?
Key differences:
DNA repair mechanisms
Control of blood flow, hemostasis
Immune system status
12
13. Closer to the disease process
Downstream of multiple pathways and integrate information
“Decision-making”
Used by clinicians to guide therapy - Provide clinical “line of site”
Predictive
Why Translational Biomarkers?
mRNA,
epigenome
Phospho-sites,
intracellular proteins,
metabolome
Cell surface,
secreted molecules
13
16. • Challenges
- Cells and assays are expensive
- Primary cells (all cell-based assays!) are variable
- Very large number of assay components / choices
• Cell types, media, additives, time points, endpoints
Experimental Design
16
17. • Solutions
- Automation
• Microwell plate-based
- Standardized methods
• Quality management system (SOPs)
• Strict assay acceptance criteria
- Incorporate methods to reduce variability
• Cells from pooled donors, prequalified
• Normalize data within plate (Log10 ratio of
compound/vehicle)
• 6+ vehicle replicates, two positive controls per plate
Experimental Design
17
18. • Compromises:
- Single well per endpoint, but:
• Multiple concentrations (4+) per compound
• Multiple assay systems per compound
• Multiple endpoints per assay system
- Single timepoint
• Suboptimal for some endpoints, but optimal for most
endpoints (24 hr – 6 days)
- Pauciparameter (7-22 endpoints per assay system), but:
• Highly informative disease biomarker endpoints
Experimental Design
18
19. BioMAP Profile of Positive Control
• Colchicine is an inhibitor of microtubules
- It is active in every system and used as a positive control on every plate
• Colchicine profile has a distinctive pattern of activities or “shape”
BioMAP Systems
Readout Parameters (Biomarkers)
Cytotoxicity Readouts
Colchicine 1.1 μM
Logexpressionratio
(Drug/DMSOcontrol)
Vehicle Control
(no drug)
95%
significance
envelope
19
20. Reproducibility of Profiles
• 16 Experiments over many months
• Pairwise correlation of profiles (Pearson’s) were > 0.8
BioMAP Systems
Readout Parameters (Biomarkers)
Houck, K.A., J. Biomolecular Screening, 2009, 14:1054-66.20
Logexpressionratio
(Drug/DMSOcontrol)
Vehicle Control
(no drug)
95%
significance
envelope
21. • Assess cytotoxicity in primary human cells
- Cytotoxicity mechanisms are cell type and activation dependent
- Note: cytotoxicity is a confounder
• Flag compounds (concentrations) that are overtly cytotoxic
• Analyze overall activity profiles
- Profile characteristics
- Unsupervised and supervised approaches to compare profiles
• Focus on individual endpoints
- Correlate to external data
- Build an understanding of clinical mechanisms
What Can We Do With BioMAP Profile Data?
21
22. Types of BioMAP Profiles
InactiveActive – Sharp dose-response
Active – Dose resistantActive – Selectively
22
23. Rapamycin (mTOR) Genistein (multi-target)
Dose Resistance
A Profile “Characteristic”
• “Dose resistant” compounds have similar activity profiles over a
wide range of concentrations
- No sharp activity jumps; Rapamycin > Genistein
• Characteristic of approved drugs & target-selective compounds
- Rapamycin is highly selective for mTOR; Genistein has multiple targets
- The dose resistance index of Rapamycin is > 60,000x
23
24. BioMAP Profiling: Example Profile
Reference p38 MAPK Inhibitor
Logexpressionratio
(Drug/DMSOcontrol)
Control (no drug)
99%
significance
envelope
BioMAP Systems
Readout Parameters (Biomarkers)
Dose
Response
Cytotoxicity Readouts
24
This profile shows dose-resistance – similar over a range of
concentrations
25. BioMAP Profiling: Example Profile
Reference p38 MAPK Inhibitor
Logexpressionratio
(Drug/DMSOcontrol)
25
Activities relevant to the role of p38 in monocyte / Th1-type inflammation
p38 kinase is important for Th1-dependent inflammatory responses
Takanami-Ohnishi Y, et al., Essential role of p38 mitogen-activated protein kinase
in contact hypersensitivity. J Biol Chem. 2002, 277:37896-903.
IL-8
HLA-DR
Monocyte
activation
IL-6IL-1aCD38
HLA-DR
TNF-a
26. BioMAP Profiling: Example Profile
Reference p38 MAPK Inhibitor
Logexpressionratio
(Drug/DMSOcontrol)
26
Activities relevant to anti-thrombotic effects of p38 inhibitors
Tissue factor is the primary cellular initiator of coagulation
p38α deficiency impairs thrombus formation
Sakurai K, et al. Role of p38 mitogen-activated protein kinase in thrombus
formation. J Recept Signal Transduct Res. 2004;24(4):283-96.
Tissue
Factor
27. BioMAP Profiling: Example Profile
Reference p38 MAPK Inhibitor
Logexpressionratio
(Drug/DMSOcontrol)
27
Activities relevant to side effects – clinical finding: skin rash
Upregulation of VCAM and ITAC are characteristic of skin hyperreactivity
Melikoglu M, et al., Characterization of the divergent wound-healing responses
occurring in the pathergy reaction and normal healthy volunteers. J Immunol.
2006, 177:6415-21.
ITAC
VCAM
MMP1
VCAM
28. 28
BioMAP® Data Analysis
Predictive
Informatics Tools
Custom informatics tools are
used to predict clinical outcomes
• Unsupervised Analyses
- Similarity Search of our reference
database
- Clustering
• Supervised Analyses
- Computational models (classifiers)
for mechanism of action
29. 29
BioMAP® Reference Database
BioMAP®
Reference Database
Biomarker responses to drugs
are stored in the database
>3000 drugs
• More than 3000 agents
- Drugs – Clinical stage, approved, and failed
- Experimental Chemicals - Research tool
compounds, environmental chemicals,
nanomaterials
- Biologics – Antibodies, cytokines, factors,
peptides, soluble receptors
• Availability of reference data
- EPA ToxCast and selected reference data
are published and have been made
available (Houck, 2009; Berg, 2010; Berg,
2013; Kleinstreuer, 2014)
30. Similarity Analysis of Profiles
Highly correlated Similar
Pearson’s correlation of r > 0.7
Low correlation Not similar
Pearson’s correlation of r < 0.7
30
36. Building Support Vector Machine Classifiers
• 88 Compounds
• 28 Target/Pathway
mechanisms
• 1-8 concentrations
• 327 Profiles
• 84 endpoints (8 BioMAP
Systems)
• Support Vector Machine
• 2-class models
• Mechanism class versus “Null”
set
• Result = Decision Value (DV)
• PPV – positive predictive value
(fraction of profiles that are correctly
classified)
• PPV = TP / (TP + FP))
• Sensitivity (fraction of profiles that
are assigned to the class)
• Sensitivity = TP / (TP + FN))
Mitochondrial
Inhibitor
Microtubule
Stabilizer Hsp90 Inhibitor
Classifier Performance: Examples
PDE IV
Inhibitor
Generate Data
Set
Build
Classifiers
Test Performance
of Classifiers
Berg, Yang & Polokoff, 2013, J. Biomol Screen. 18:1260.36
37. • AhR agonist (Aryl Hydrocarbon)
• Calcineurin
• EGFR (Epidermal Growth Factor R)
• SERCA (SR Ca++ ATPase)
• EP agonist
• Estrogen R agonist
• Glucocorticoid R agonist
• H1R Antagonist (Histamine)
• HDAC
• HMG-CoA-Reductase
• Hsp90 Inhibitor
• IKK2
• IL-17 R agonist
• JAK
Confidential37
List of Classifiers (SVM Mechanism Models)
• MEK
• Microtubule Disruptor
• Microtubule Stabilizer
• Mitochondrial Inhibitor
• mTOR
• p38 MAPK
• PDE IV (Phosphodiesterase
• PI3K
• PKC (c+n)
• Proteasome
• RAR-RXR agonist
• Src family
• TNF (Tumor Necrosis Factor)
• VDR agonist (Vitamin D R)
Berg, Yang & Polokoff, 2013, J. Biomol Screen. 18:1260.
38. • Compound characterization
- Broad biological fingerprint
- Cell types, pathways, possible clinical indications
• Mechanism of action
- Triage hits from phenotypic drug discovery programs
- Unexpected off-targets (toxicity)
• Support therapeutic hypotheses
- Compare to competitor molecules, clinical standards of care
- Identify translational biomarkers
Applications
38
40. EPA ToxCastTM Program – BioSeek
Goal is identification of in vitro assays that can help
forecast in vivo toxicity of environmental and other
agents (including pharmaceuticals)
40
Task Order Compound Number Compound Type
TO1 320 Environmental compounds
TO2 500 Environmental compounds
TO3 200 Environmental and Failed Pharma Compounds
TO4 39 Nanomaterials
TO5 31 Nanomaterials
TO6 100 Failed Pharma Compounds, etc.
TO7 39 Nanomaterials
Total 1229
40
Houck, K.A., J. Biomolecular Screening, 2009, 14:1054-66;
Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.
41. Chemical Groups & Classes in ToxCast
Most active
Least active
41
Overall: 73% Active
(33 – 83%)
Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.
42. Results of Supervised Analysis
Performance of SVM Mechanism Classifiers
Mechanism Class1 Number of
Compounds
Correctly
Assigned
% Comment
p38 MAPK Inhibitor 2 2 100%
Estrogen R Agonist 10 6 60%
Not classified: meso-Hexestrol, 4-
nonylphenol and diethystilbestrol
HMG-CoA Reductase Inhibitor 3 3 100%
Histamine R1 Antagonist 1 1 100%
Microtubule Inhibitor 2 1 50% Herbicides
GR Agonist 3 3 100%
Mitochondrial Inhibitor 2 2 100% Fungicides
PDE IV Inhibitor 8 6 75%
RAR/RXR Agonist 2 2 100%
Total 33 26 79%
• 1Mechanisms for which classifiers were available and mechanisms were known
- Dataset: Kleinstreuer, Nature Biotechnology, 2014, 32:583
- Classifiers: Berg, Yang and Polokoff, JBS, 2013, 18:1260
42
43. Unsupervised Analysis (Self Organizing Maps)
AhR Phenotypic Signature
• Phenotypic signature of
compounds in SOM cluster #57
- Box and whisker plot for cluster
57 representing a signature for
AhR activation
• Confirmation of AhR activity
- 85% of members of clusters 57,
67 (adjacent in the 10X10 SOM)
were active in an AhR reporter
gene assay (examples shown
here).
Tissue Factor
Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.43
44. Unsupervised Analysis (Self Organizing Maps)
Estrogen R Actives: Phenotypic Signatures
• Two clusters of chemicals defined by their BioMAP signatures
- Blue = Estradiol, Estrogen Receptor Agonists
- Red = Estrogen Receptor Antagonists, “Selective Estrogen R Modulators”
• Increased levels of Tissue Factor by SERMs and ER antagonists
Kleinstreuer, 2014, Nature Biotechnology, 32:583-91.
Estrogen
Receptor
Antagonists
Estrogen
Receptor
Agonists
Tissue Factor
44
46. • Pathologic setting – aberrant coagulation thrombosis
- The formation of a blood clot (coagulation) within a vein
- Deep vein thrombosis (DVT), stroke
- Pulmonary embolism thrombi break off and get lodged in the
lung
Thrombosis
SMC
Endothelial cells
Vessel Lumenplatelets in fibrin clot
46
48. • Associated with:
- Exposure to Smoking & Pollution
• Polycyclic aromatic hydrocarbons (“Aryl Hydrocarbons”)
- Contraceptives, hormonal replacement therapy
- Various other drugs
• mTOR inhibitors (everolimus)
• 2nd generation anti-psychotics
Thrombosis-Related Side Effects
48
49. • Aryl Hydrocarbon receptor agonists
- PAHs, Benz(a)anthracene
- Smoking (Cigarette smoke extract)
• mTOR inhibitors
- Everolimus (Baas, 2013, Thromb Res 132:307)
• Anti-Estrogens / SERMS, oral contraceptives
- Tamoxifen, Clomiphene, Cyproterone
• Second generation anti-psychotics
- Clozapine
• Others
- Crizotinib
Mechanisms / Drugs Associated with
Thrombosis-Related Side Effects
All show increased Tissue Factor levels in 3C and LPS Systems
49
50. • Search our reference database for all compounds / test
agents that increase TF in the 3C system
- What are the mechanisms represented?
- Do they share any common biology?
• Issues
- Large chemical-biology datasets will have errors
• Inactive concentrations, toxic concentrations, variability
- How do we increase our confidence?
• Require compound effects at more than one concentration
• Effect size >20% (4 SD)
• Multiple compounds with same target mechanism
Is There A Connection?
50
52. Mechanisms that Increase TF
Test Agents Mechanism
Confidence in
Mechanism
2-Mercaptobenzothiazole AhR agonist High
3-Hydroxyfluorene AhR agonist High
Benzo(b)fluoranthene AhR agonist High
C.I Solvent yellow 14 AhR agonist High
FICZ AhR agonist High
Abiraterone CYP17A Inhibitor High
Ketoconazole CYP17A Inhibitor High
Clomiphene citrate Estrogen R Antagonist High
Histamine H1R agonist High
Histamine Phosphate H1R agonist High
Cobalt(II) Chloride Hexahydrate HIF-1α Inducer High
Tin(II) Chloride HIF-1α Inducer High
Chloroquine Phosphate Lysosome Inhibitor High
Primaquine Diphosphate Lysosome Inhibitor High
Temsirolimus mTOR Inhibitor High
Torin-1 mTOR Inhibitor High
Torin-2 mTOR Inhibitor High
Bryolog PKC activator High
Bryostatin PKC activator High
Bryostatin 1 PKC activator High
Phorbol 12-myristate 13-acetate PKC activator High
Phorbol 12,13-didecanoate PKC activator High
Picolog PKC activator High
3,5,3-Triiodothyronine Thyroid H R agonist Good
Concanamycin A Vacuolar ATPase Inhibitor Good
Mifamurtide NOD2 agonist Good
Oncostatin M OSM R agonist Good
Ethanol Organic Solvent Good
PAz-PC Oxidized phospholipid Good
Z-FA-FMK Cysteine protease Inhibitor Good
8-Hydroxyquinoline Chelating agent Unknown
A 205804 ICAM, E-selectin inhibitor Unknown
AZD-4547 FGFR Inhibitor Unknown
Crizotinib ALK, c-met Inhibitor Unknown
Desloratadine H1R antagonist Unknown
Dodecylbenzene Industrial chemical Unknown
Fenaminosulf Fungicide Unknown
GDC-0879 B-Raf Inhibitor Unknown
GW9662 PPARγ agonist Unknown
Imatinib PDGFR, c-Kit, Bcr-Abl Inhibitor Unknown
KN93 CaMKII Inhibitor Unknown
Linoleic Acid Ethyl Ester Fatty Acid Unknown
Mancozeb Fungicide Unknown
MK-2206 AKT Inhibitor Unknown
Mometasone furoate GR agonist Unknown
N-Ethylmaleimide Alkylating agent Unknown
PP3 SRC Kinase Inhibitor Unknown
Primidone GABA R agonist Unknown
Sulindac Sulfide NSAID Unknown
Terconazole Anti-fungal Unknown
Tris(1,3-dichloro-2-propyl) phosphate Flame retardant Unknown
TX006146 Unknown Unknown
TX006237 Unknown Unknown
TX011661 Unknown Unknown
U-73343 Unknown Unknown
UO126 MEK Inhibitor Unknown
ZK-108 PI-3K Inhibitor (βγ-selective) Unknown
Mechanisms that Increase TF
AhR Agonist
CYP17A Inhibitor
Estrogen R Antagonist
H1R Agonist
HIF-1α Inducer
Lysosomal Inhibitor
mTOR Inhibitor
PKC Activator
Thyroid H R Agonist
Vacuolar ATPase Inhibitor
NOD2 Agonist
OSM R Agonist
52
53. Mechanisms that Increase TF
Mechanisms that Increase TF
AhR Agonist
CYP17A Inhibitor
Estrogen R Antagonist
H1R Agonist
HIF-1α Inducer
Lysosomal Inhibitor
mTOR Inhibitor
PKC Activator
Thyroid H R Agonist
Vacuolar ATPase Inhibitor
NOD2 Agonist
OSM R Agonist
Implicate Autophagy
53
54. Autophagy
• Cellular response to nutrient deprivation
• Also contributes to recycling of dysfunctional
organelles, handling of protein aggregates, bacteria and
viruses54
60. • Summary
- Compounds that increase TF are associated with thrombosis
related side effects
- Compounds that increase TF also increase autophagic vacuoles
(increase formation or decrease breakdown)
- Mechanistic Hypothesis: thrombosis-related side effects are
associated with alterations in the process of autophagy that
increase TF cell surface levels
• Take home message:
- This case study illustrates how chemical biology datasets,
combined with external knowledge, can give rise to higher level
mechanistic understanding of toxicity mechanisms
Tissue Factor, Autophagy & Thrombosis
60
61. Adverse Outcome Pathway Framework
MIE
Key
Event
Adverse
Outcome
Key
Event
Key
Event
Molecular
Initiating Event Clinical Effect
• Framework for integrating mode of action hypotheses to
outcomes for chemical risk assessment (OECD)
- http://www.oecd.org/chemicalsafety/testing/adverse-outcome-pathways-
molecular-screening-and-toxicogenomics.htm
• Focused on the clinical outcome
- Anchored at both ends
61
62. AOP for DVT
MIE
Key
Event
Adverse
Outcome
Inhibition of
mTOR
Upregulation
of Tissue
Factor
Deep Vein
Thrombosis
Initiation of
Coagulation
Key
Event
Key
Event
Molecular
Initiating Event Clinical Effect
Increase in
Autophagic
Vacuolization
62
63. AOP for DVT
MIE
Key
Event
Adverse
Outcome
Inhibition of
mTOR
Upregulation
of Tissue
Factor
Deep Vein
Thrombosis
Initiation of
Coagulation
Key
Event
Key
Event
Molecular
Initiating Event Clinical Effect
MIE
Activation of
AhR
Increase in
Autophagic
Vacuolization
Key
Event
Inhibition of
NPC1
Key
Event
HDF3CGF
In vitro
disease model
3C
3C 4H LPS
Endothelial
Cells
Endothelial
Cells
PBMC +
Endothelial
Cells
P
En
Th1 Th2 TLR4
BioMAP System
Primary Human Cell
Types
Stimuli
! ! !
63
65. • Challenges for studying drug combinations:
- System must include both targets
- Physiologically relevant setting (ideally all human)
- Suitably robust to capture combination effects
• Case Example
- BioMAP Oncology systems that model tumor-host
microenvironments
- Trametinib (MEK kinase inhibitor) + Dabrafenib (Braf inhibitor)
• Combination approved for treatment of melanoma
Drug Combinations
65
69. Dabrafenib (B-raf) Trametinib (MEK) Dabrafenib +Trametinib
• Combination effects of Dabrafenib (B-raf) and Trametinib (MEK)
- Tumor cell marker (CEACAM5) is reduced only in the combination (green
arrow)
- Consistent with the combination being more efficacious against tumors in vivo
69
Combination Study Example:
B-Raf + MEK Inhibitor
70. Dabrafenib (B-raf) Trametinib (MEK) Dabrafenib +Trametinib
• Combination effects of Dabrafenib (B-raf) and Trametinib (MEK)
- Tumor cell marker (CEACAM5) is reduced only in the combination
- Consistent with the combination being more efficacious against tumors in vivo
- Reduced levels of Inflammatory endpoints; collagen III (grey arrows)
- Consistent with reduced Trametinib-related skin side effects (Flaherty, 2012,
NEJM 367:1694).
70
Combination Study Example:
B-Raf + MEK Inhibitor
71. • Chemical profiling in human cell systems generates
activity profiles that can be used to:
- Group chemicals into bioactivity classes
- Generate MoA hypotheses
- Identify activities that may correlate with in vivo outcomes
• High throughput in vitro data is most informative when
combined with external information
- Known targets
- In vivo bioactivities
Summary
Confidential71
72. • Applications for predicting in vivo effects must
also consider:
- Exposure - level and route
- Distribution
- Metabolism
- Human variability
Challenges and Considerations
Confidential72
73. • BioSeek
- Mark A. Polokoff
- Dat Nguyen
- Xitong Li
- Antal Berenyi
- Alison O’Mahony
- Jian Yang (Oracle)
• UCSF
- Kevan Shokat
Acknowledgements
• EPA
- Keith Houck
- Nicole Kleinstreuer
- Richard Judson
• Support
- NIH/NIAID (SBIR)
- EPA (EP-D-12-047, EP-
W-07-039)
73
74. Contact:
Ellen L. Berg, PhD
Scientific Director
BioSeek, a division of DiscoveRx
eberg@bioseekinc.com
Editor's Notes
The complexity of biological systems makes it difficult to predict outcomes from both target-based as well as phenotypic drug discovery efforts.
The BioMAP platform of cell-based assay platform designed to include more of the biological complexity of human disease, but yet in a practical format with sufficient throughput to be used in early discovery.
So what do we mean by biological complexity?
The complexity of biological systems makes it difficult to predict outcomes from both target-based as well as phenotypic drug discovery efforts.
The BioMAP platform of cell-based assay platform designed to include more of the biological complexity of human disease, but yet in a practical format with sufficient throughput to be used in early discovery.
So what do we mean by biological complexity?