Jornada TOX® is a company that provides computational chemistry services for drug discovery, including receptor-based virtual screening, QSAR modeling, and macromolecular modeling, through their Intelligent Discovery, Intelligent Software, and Intelligent Knowledge business lines with offices in Barcelona, Heidelberg, and Cambridge. They have worked on over 100 research projects involving targets such as kinases and ion channels across therapeutic areas like oncology and cardiology using techniques like docking and molecular dynamics simulations. Jornada TOX® collaborates with academic partners and software companies and sells third party software for knowledge management in life sciences.
A significant amount of time could be saved by cutting out the unnecessary steps from traditional cloning and moving into gene synthesis. Gene synthesis has become a costeffective, time- and resource-saving method for obtaining nearly any desired DNA construct with 100% accuracy. It outperforms conventional molecular biology techniques in terms of time and cost, while providing equivalent or better expression performance, and construct stability and quality. GeneArt® gene synthesis tools gobeyond traditional synthesis and enable expression optimization and maximum performance. Watch this webinar with audio at: http://owl.li/jppYn
BRINGING LEADING EDGE PHARMACEUTICAL CAPABILITIES TO COSMETICS
Novel IP Faster time to market Collaboration opportunities David Pompliano, CEO, Bioleap Inc
SBS 2011: Sensitive Cell-based and Biochemical Assays Using Epic(R) Label-fre...PerkinElmer, Inc.
Here we show how the PerkinElmer EnSpire®Multimode Plate Reader with Corning®Epic®label-free technology can be used in 96-and 384-well microplate formats to non-invasively identify and characterize multiple G protein-coupled receptor (GPCR) pathways in living cells using an orthogonal approach. Furthermore, this orthogonal platform enables the use of both label-free and labeled technologies to comprehensively identify and characterize target and ligand behavior in both cell-based and biochemical assays, with greater confidence. By successfully monitoring the ligand-induced dynamic mass redistribution (DMR) in living cells and the ligand-dependent response interrogating protein:proteinand protein:smallmolecule biomolecularinteractions, we demonstrate that this label-free technology is a comprehensive and versatile tool for GPCR research enabling the generation of physiologically-relevant data.
A significant amount of time could be saved by cutting out the unnecessary steps from traditional cloning and moving into gene synthesis. Gene synthesis has become a costeffective, time- and resource-saving method for obtaining nearly any desired DNA construct with 100% accuracy. It outperforms conventional molecular biology techniques in terms of time and cost, while providing equivalent or better expression performance, and construct stability and quality. GeneArt® gene synthesis tools gobeyond traditional synthesis and enable expression optimization and maximum performance. Watch this webinar with audio at: http://owl.li/jppYn
BRINGING LEADING EDGE PHARMACEUTICAL CAPABILITIES TO COSMETICS
Novel IP Faster time to market Collaboration opportunities David Pompliano, CEO, Bioleap Inc
SBS 2011: Sensitive Cell-based and Biochemical Assays Using Epic(R) Label-fre...PerkinElmer, Inc.
Here we show how the PerkinElmer EnSpire®Multimode Plate Reader with Corning®Epic®label-free technology can be used in 96-and 384-well microplate formats to non-invasively identify and characterize multiple G protein-coupled receptor (GPCR) pathways in living cells using an orthogonal approach. Furthermore, this orthogonal platform enables the use of both label-free and labeled technologies to comprehensively identify and characterize target and ligand behavior in both cell-based and biochemical assays, with greater confidence. By successfully monitoring the ligand-induced dynamic mass redistribution (DMR) in living cells and the ligand-dependent response interrogating protein:proteinand protein:smallmolecule biomolecularinteractions, we demonstrate that this label-free technology is a comprehensive and versatile tool for GPCR research enabling the generation of physiologically-relevant data.
The Notion: 5pt BRAND conversation is a brand conversation that is designed to engage consumers with products and services. Effective communication design creates a dialogue and encourages the consumer to start a conversation about their experience in the brand community.
The CiToxLAB Group offers a comprehensive range of preclinical services and specialty safety evaluation services to meet the needs of pharmaceutical, biotechnology and chemical companies worldwide.
Our four CiToxLAB international facilities in France, Canada, Denmark and Hungary carry out studies in general and reproductive toxicology, carcinogenicity, bioanalysis, immunology and safety pharmacology. The group has special expertise in areas such as inhalation or intra-nasal toxicology, radiation safety (ARS), NHPs and minipigs. Environmental studies are a further specialty including ecotoxicology and those related to REACH regulations.
Together with partners such as Atlanbio (St Nazaire, France) Stemina (Madison, USA) and Biomodels (Boston, USA), CiToxLAB also provides services such as clinical bioanalysis, embryonic stem cell biomarker discovery and customized preclinical efficacy models.
CiToxLAB now offers flexibility, direct contact to scientists, easy access to management and local, smart-sized facilities. Aggressive scheduling, increased size and capacity, turnkey solutions of global packages supported by project managers and broader geographic proximity are core values of CITOXLAB.
Contact our team of experts: www.citoxlab.com
II-PIC 2017: Drug Discovery of Novel Molecules using Chemical Data Mining toolDr. Haxel Consult
Muthukumarasamy Karthikeyan (CSIR-National Chemical Laboratory, India)
Surojit Sadhu (Advent Informatics, India)
Virtual screening (VS) and chemical data extracted from evidence based sources are the backbone of computational drug discovery workflow, an indispensable component in all drug design programs. It involves a host of modelling techniques from simple similarity search methods to advanced algorithms for finding the accurate bioactive conformation of a molecule to bind to its corresponding target. Chemoinformatics supports virtual screening at multiple levels during the lead optimization stage by suggesting suitable filters for numerous screenings by utilizing the power of data integration from multiple sources and derived knowledge that is essential for decision support in drug discovery and development. It is therefore pertinent to develop tools, data and emerging methods in chemoinformatics to fully understand their role and applications in virtual screening. Recently we have developed chemical informatics tools to assist drug discovery by chemical data extraction from literature, virtual library design, analysis and screening methods on selected case studies.
Cadd and molecular modeling for M.PharmShikha Popali
THE CADD IS FOR THE DRUG DEVELOPMENT THE DIFFERENT STRATEGIES ARE MENTIONED LIKE QSAR MOLECULAR DOCKING, THE DIFFERENT DIMNSIONAL FORMS OF QSAR , THE ADVANCE SAR of it.
The Notion: 5pt BRAND conversation is a brand conversation that is designed to engage consumers with products and services. Effective communication design creates a dialogue and encourages the consumer to start a conversation about their experience in the brand community.
The CiToxLAB Group offers a comprehensive range of preclinical services and specialty safety evaluation services to meet the needs of pharmaceutical, biotechnology and chemical companies worldwide.
Our four CiToxLAB international facilities in France, Canada, Denmark and Hungary carry out studies in general and reproductive toxicology, carcinogenicity, bioanalysis, immunology and safety pharmacology. The group has special expertise in areas such as inhalation or intra-nasal toxicology, radiation safety (ARS), NHPs and minipigs. Environmental studies are a further specialty including ecotoxicology and those related to REACH regulations.
Together with partners such as Atlanbio (St Nazaire, France) Stemina (Madison, USA) and Biomodels (Boston, USA), CiToxLAB also provides services such as clinical bioanalysis, embryonic stem cell biomarker discovery and customized preclinical efficacy models.
CiToxLAB now offers flexibility, direct contact to scientists, easy access to management and local, smart-sized facilities. Aggressive scheduling, increased size and capacity, turnkey solutions of global packages supported by project managers and broader geographic proximity are core values of CITOXLAB.
Contact our team of experts: www.citoxlab.com
II-PIC 2017: Drug Discovery of Novel Molecules using Chemical Data Mining toolDr. Haxel Consult
Muthukumarasamy Karthikeyan (CSIR-National Chemical Laboratory, India)
Surojit Sadhu (Advent Informatics, India)
Virtual screening (VS) and chemical data extracted from evidence based sources are the backbone of computational drug discovery workflow, an indispensable component in all drug design programs. It involves a host of modelling techniques from simple similarity search methods to advanced algorithms for finding the accurate bioactive conformation of a molecule to bind to its corresponding target. Chemoinformatics supports virtual screening at multiple levels during the lead optimization stage by suggesting suitable filters for numerous screenings by utilizing the power of data integration from multiple sources and derived knowledge that is essential for decision support in drug discovery and development. It is therefore pertinent to develop tools, data and emerging methods in chemoinformatics to fully understand their role and applications in virtual screening. Recently we have developed chemical informatics tools to assist drug discovery by chemical data extraction from literature, virtual library design, analysis and screening methods on selected case studies.
Cadd and molecular modeling for M.PharmShikha Popali
THE CADD IS FOR THE DRUG DEVELOPMENT THE DIFFERENT STRATEGIES ARE MENTIONED LIKE QSAR MOLECULAR DOCKING, THE DIFFERENT DIMNSIONAL FORMS OF QSAR , THE ADVANCE SAR of it.
With the unprecedented growth of chemical databases incorporating up to several hundred billions of synthetically feasible chemicals, modelers are not in shortage of chemicals to process. Importantly, such "Big Chemical Data" offers humongous opportunities for discovering novel bioactive molecules. However, the current generation of cheminformatics software tools is not capable of handling, characterizing, and processing such extremely large chemical libraries. In this presentation, we will discuss the rationale and the main challenges (theoretical and technical) for screening very large repositories of compounds in the current context of drug discovery. We will present several proof-of-concept studies regarding the screening of extremely large libraries (1+ billion compounds) using our novel GPU-accelerated cheminformatics platform to identify molecules with defined bioactivity. Overall, we will show that GPU computing represents an effective and inexpensive architecture to develop, employ, and validate a new generation of cheminformatics methods and tools ready to process billions of compounds.
Development of machine learning-based prediction models for chemical modulato...Sunghwan Kim
Presented at the 2018 Research Festival at the National Institutes of Health (NIH) in Bethesda, MD (September 13, 2018).
==== Abstract ====
The retinoid X receptor (RXR) is a nuclear hormone receptor that functions as a transcription factor with roles in development, cell differentiation, metabolism, and cell death. Chemicals that interfere the RXR signaling pathway may cause adverse effects on human health. In this study, public-domain bioactivity data available in PubChem (https://pubchem.ncbi.nlm.nih.gov) were used to develop machine learning-based prediction models for chemical modulators of RXR-alpha, which is a subtype of RXR that plays a role in metabolic signaling pathways, dermal cysts, cardiac development, insulin sensitization, etc. The models were constructed from quantitative high-throughput screening (qHTS) data from the Tox21 project, using popular supervised machine learning methods (including support vector machine, random forest, neural network, k-nearest neighbors, decision tree, and naïve Bayes). The general applicability of the developed models was evaluated with external data sets from ChEMBL and the NCATS Chemical Genomics Center (NCGC). This study showcases how open data in the public domain can be used to develop prediction models for bioactivity of small molecules.
Webinar: New RMC - Your lead_optimization Solution June082017Ann-Marie Roche
The drug discovery landscape is rapidly changing and drives the need to generate leads with lower attrition rates.
In this webinar, our expert Dr. Olivier Barberan discussed how NEW Reaxys Medicinal chemistry in NEW Reaxys allows better discovery and exploration of structure activity relationship and also supports a more efficient property-based drug design approach. He covered the following:
• How has RMC being transformed into a more accessible tool for all users, allowing complex searches and workflows to be easily carried out.
• A demonstration of how more than ever RMC is the only lead-optimization solution you will need.
Using open bioactivity data for developing machine-learning prediction models...Sunghwan Kim
Presented at the 256th American Chemical Society (ACS) National Meeting in Boston, MA (August 22, 2018).
==== Abstract ====
The retinoid X receptor (RXR) is a nuclear hormone receptor that functions as a transcription factor with roles in development, cell differentiation, metabolism, and cell death. Chemicals that interfere the RXR signaling pathway may cause adverse effects on human health. In this study, open bioactivity data available at PubChem (https://pubchem.ncbi.nlm.nih.gov) were used to develop prediction models for chemical modulators of RXR-alpha, which is a subtype of RXR that plays a role in metabolic signaling pathways, dermal cysts, cardiac development, insulin sensitization, etc. The models were constructed from quantitative high-throughput screening (qHTS) data from the Tox21 project, using various supervised machine learning methods (including support vector machine, random forest, neural network, k-nearest neighbors, decision tree, and naïve Bayes). The performance of the models was evaluated with an external data set containing bioactivity data submitted by ChEMBL and the NCATS Chemical Genomics Center (NCGC). This study showcases how open data in the public domain can be used to develop prediction models for chemical toxicity.
BOC Sciences aims at developing the most accurate in silico methods to overcome bottlenecks in drug discovery and design innovative medicines to treat important disease.
The importance of data curation on QSAR Modeling: PHYSPROP open data as a cas...Kamel Mansouri
This presentation highlighted how data curation impacts the reliability of QSAR models. We examined key datasets related to environmental endpoints to validate across chemical structure representations (e.g., mol file and SMILES) and identifiers (chemical names and registry numbers), and approaches to standardize data into QSAR-ready formats prior to modeling procedures. This allowed us to quantify and segregate data into quality categories. This improved our ability to evaluate the resulting models that can be developed from these data slices, and to quantify to what extent efforts developing high-quality datasets have the expected pay-off in terms of predicting performance. The most accurate models that we build will be accessible via our public-facing platform and will be used for screening and prioritizing chemicals for further testing.
REGLAMENTO (UE) N o 640/2012 DE LA COMISIÓN de 6 de julio de 2012 que modifica, con vistas a su adaptación al progreso técnico, el Reglamento (CE) n o 440/2008, por el que se establecen métodos de ensayo de acuerdo con el Reglamento (CE) n o 1907/2006 del Parlamento Europeo y del Consejo, relativo al registro, la evaluación, la autorización y la restricción de las sustancias y preparados químicos (REACH)
En UTOX hemos definido 6 fichas técnicas para los 6 sectores mayoritarios de actuación en toxicología, las cuales muestran nuestro ámbito de actuación para cada uno de ellos.
En UTOX hemos definido 6 fichas técnicas para los 6 sectores mayoritarios de actuación en toxicología, las cuales muestran nuestro ámbito de actuación para cada uno de ellos.
En UTOX hemos definido 6 fichas técnicas para los 6 sectores mayoritarios de actuación en toxicología, las cuales muestran nuestro ámbito de actuación para cada uno de ellos.
En UTOX hemos definido 6 fichas técnicas para los 6 sectores mayoritarios de actuación en toxicología, las cuales muestran nuestro ámbito de actuación para cada uno de ellos.
En UTOX hemos definido 6 fichas técnicas para los 6 sectores mayoritarios de actuación en toxicología, las cuales muestran nuestro ámbito de actuación para cada uno de ellos.
More from La unidad de Toxicología Experimental y Ecotoxicología (UTOX-PCB) (15)
2. Business lines
Intelligent Discovery
We carry out computational chemistry projects using our self-
developed and third party technologies for drug discovery, cosmetics
and nutraceuticals.
Intelligent Software
We offer advanced software development solutions for companies
and institutions working in life sciences.
Intelligent Knowledge
We commercialize third party software application for knowledge
management focusing on life sciences.
3. Offices: Clients: Markets:
• Pharmaceutical companies • Europe
Barcelona Science Park
Spain • Biotech companies • USA
• Life Sciences institutions: • South America: Mexico, Brazil
Hospitals, Universities, • Asia: Korea
Technologie Park Heidelberg Technological Transfer Offices
Germany
Collaborations:
Synthesis and Medicinal Chemistry Software Partners
BioPark Hertfordshire
United Kingdom
185 Alewife Brook Parkway
Cambridge, MA
USA
5. > 100 Research Projects in 5 years
Therapeutic Areas
Type of targets
6. Determination of mechanism of action
Computer-aided Hit to Lead optimization
ADME/Tox prediction
Solving physicochemical problems
Extension of patent protection
Identification of new active compounds Drug Reprofiling
Determination of inhibitors Identification of back-ups
Identification of off-targets
Selectivity Studies
7. Molecular Dynamics Allosterics
Pharmacophor Modeling Prof. Alejandro Pankovich, Xavier Daura
Universitat Autònoma de Barcelona
Bio-informatic tools
8. PREDICTIVE
TOXICOLOGY/PHARMACOLOGY
Initiatives
Computational Toxicology Research Program (CompTox)
USA – environmental protection agency (http://www.epa.gov/heasd/edrb/comptox.html)
Predictive Toxicology
Europe – joint research center (http://ihcp.jrc.ec.europa.eu/our_labs/predictive_toxicology)
Computational toxicology at the European Commission's Joint Research Centre
Europe Union
The methods and tools of computational toxicology form an essential and
integrating pillar in the new paradigm of predictive toxicology, which seeks
to develop more efficient and effective means of assessing chemical
toxicity, while also reducing animal testing.*
*Mostrag-Szlichtyng A., Zaldivar Comenges JM, Worth AP. Computational toxicology at the European
Commission's Joint Research Centre (2010) Expert Opin Drug Metab Toxicol, 6(7), 785-92.
9. Molecules used as pharmaceuticals/active ingredients
3-D structure
2-D structure
Biological Function
Biological molecules as Sugars, DNA & Proteins
3-D structure
Primary sequence
10. Molecules with measured Cardiovascular Toxicity
3-D structure
2-D structure
Cardiovascular Toxicity
hERG & KCQN1 is responsible for Cardiovascular Toxicity
3-D structure
11. DISCOVERY PROJECTS
Receptor-based Virtual Screening
Determination of inhibitors
Only receptor’s information is needed
Hit to lead optimization
Determines Binding Energy and Binding Design more potent ligands
Constants Kd (mM, μM and nM) Drug Reprofiling
Obtains Structural Data Determination of MOA
High throughput screening
Based on Docking
Docking algorithms based on Vina1 & Autodock 4.22
Binding Energies & Binding Modes
Biological Target
+ Molecules
Receptor
Active -13kcal/mol
Expected binding mode
HMG-CoA Reductase -6kcal/mol
Inactive Other binding mode
1 O Trott, AJ Olson J Comput Chem. 2010, 31, 455–461.
2 G Morris, D Goodsell, R Halliday, R Huey, W Hart, R Belew, A Olson J Comput Chem. 1998, 19, 1639–62.
16. Drug Reprofiling Macromolecular Modeling
Hit to Lead
Determination of MOA
DB and Collaborative Tools Management
Hit Identification
Training on Macromolecular Modeling
17. Parc Científic de Barcelona Technologie Park Heidelberg
C/ Baldiri Reixac, 4-8 Im Neuenheimer Feld 582
08028 Barcelona 69120 Heidelberg
Spain Germany
T: +34 934 034 551 T: +49 (0) 6221 5025716
BioPark USA
Broadwater Road, Welwyn Garden City 185 Alewife Brook Parkway, #410
Hertfordshire AL7 3AX, United Kingdom Cambridge, MA 02138
T: +44 (0) 1707 356100
Sales & Business Development Department
Jascha Blobel, PhD jblobel@intelligentpharma.com
Anna Serra, PhD aserra@intelligentpharma.com
Irene Meliciani, PhD imeliciani@intelligentpharma.com
www.intelligentpharma.com