This presentation summarizes some early efforts on an open drug discovery collaboration between scientists in Brazil and the US. The amazing virus images were created by John Liebler and can be licensed from him http://www.artofthecell.com/animation/will-the-real-zika-virus-please-stand-up
The homology models were created with Swiss Model by Sean Ekins:
Marco Biasini, Stefan Bienert, Andrew Waterhouse, Konstantin Arnold, Gabriel Studer, Tobias Schmidt, Florian Kiefer, Tiziano Gallo Cassarino, Martino Bertoni, Lorenza Bordoli, Torsten Schwede. (2014). SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Research; (1 July 2014) 42 (W1): W252-W258; doi: 10.1093/nar/gku340.
Arnold K., Bordoli L., Kopp J., and Schwede T. (2006). The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics, 22,195-201.
Kiefer F, Arnold K, Künzli M, Bordoli L, Schwede T (2009). The SWISS-MODEL Repository and associated resources. Nucleic Acids Research. 37, D387-D392.
Guex, N., Peitsch, M.C., Schwede, T. (2009). Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: A historical perspective. Electrophoresis, 30(S1), S162-S173.
New Target Prediction and Visualization Tools Incorporating Open Source Molec...Sean Ekins
SLAS talk 2015 on TB Mobile 2.0 a mobile app using open source fingerprints and Bayesian machine learning algorithm for tuberculosis target prediction.
Why there needs to be open data for ultra-rare and rare disease drug discoverySean Ekins
ACS presentation 11th Aug San Francisco on the need for open data in ultra rare and rare diseases. Describes efforts of parent/ patient advocates to fund drug discovery research. Also it describes software for open collaboration and what needs to be done to create software champions for rare diseases. Mentions diseases like Sanfilippo Syndrome, giant axonal neuropathy and Charcot Marie Tooth. Apps like ODDT are also mentioned as a means to share data.
This presentation summarizes some early efforts on an open drug discovery collaboration between scientists in Brazil and the US. The amazing virus images were created by John Liebler and can be licensed from him http://www.artofthecell.com/animation/will-the-real-zika-virus-please-stand-up
The homology models were created with Swiss Model by Sean Ekins:
Marco Biasini, Stefan Bienert, Andrew Waterhouse, Konstantin Arnold, Gabriel Studer, Tobias Schmidt, Florian Kiefer, Tiziano Gallo Cassarino, Martino Bertoni, Lorenza Bordoli, Torsten Schwede. (2014). SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Research; (1 July 2014) 42 (W1): W252-W258; doi: 10.1093/nar/gku340.
Arnold K., Bordoli L., Kopp J., and Schwede T. (2006). The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics, 22,195-201.
Kiefer F, Arnold K, Künzli M, Bordoli L, Schwede T (2009). The SWISS-MODEL Repository and associated resources. Nucleic Acids Research. 37, D387-D392.
Guex, N., Peitsch, M.C., Schwede, T. (2009). Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: A historical perspective. Electrophoresis, 30(S1), S162-S173.
New Target Prediction and Visualization Tools Incorporating Open Source Molec...Sean Ekins
SLAS talk 2015 on TB Mobile 2.0 a mobile app using open source fingerprints and Bayesian machine learning algorithm for tuberculosis target prediction.
Why there needs to be open data for ultra-rare and rare disease drug discoverySean Ekins
ACS presentation 11th Aug San Francisco on the need for open data in ultra rare and rare diseases. Describes efforts of parent/ patient advocates to fund drug discovery research. Also it describes software for open collaboration and what needs to be done to create software champions for rare diseases. Mentions diseases like Sanfilippo Syndrome, giant axonal neuropathy and Charcot Marie Tooth. Apps like ODDT are also mentioned as a means to share data.
CDD: Vault, CDD: Vision and CDD: Models software for biologists and chemists ...Sean Ekins
A perspective on 12 yrs of CDD and developing products and collaborations.
A presentation given at the ACS meeting in San Diego - small business section
A potential vision of the future "the ncecessary", developed for a presentation at to be provocative. The goal was to think about the near and far future and put it into context with some of the science happening now as well as disruptive steps happening in rare disease science funding. Several slides highlight 'the ideal situation'.
Ensuring Chemical Structure, Biological Data and Computational Model Quality
A talk given at SLAS 2016 mon Jan 25th in San Diego
covers published work and recent forays with BIA 10-2474
Le web sémantique pour mieux anticiper le futurSylvain Gateau
Après le web 1.0 et le web 2.0, place au web sémantique. Jusque là encore unilatérale, la relation homme / machine prend une nouvelle dimension avec la sémantisation des contenus : les machines sont désormais capables de comprendre et d’exploiter le contenu. Pour notre plus grand bien ?
Le web sémantique est en marche pour nous préparer au futur. Des courants de pensées, tels que le « Future friendly web », prônent un web propre, structuré, et véhiculant du contenu porteur de sens, prêt à s’adapter et à être diffusé n’importe où, n’importe quand. À la croisée des Sciences Sociales et Humaines et des Sciences de l’Information et de la Communication, le web sémantique est donc sur le point de redéfinir nos relations communicationnelles ainsi que l’organisation de l’écosystème numérique.
Vers de nouveaux métiers ? De nouveaux acteurs ? De nouvelles pratiques ? Une chose est sûre, c’est qu’à partir d’aujourd’hui, la machine entre un peu plus dans notre sphère intime, relationnelle et communicationnelle. Un pas de plus vers l’intelligence artificielle ?
Conférence "Optimiser son référencement Internet"Sylvie de Meeûs
- Le référencement naturel est (toujours !) le meilleur moyen d'attirer de nouveaux clients
- Le référencement ne coûte pas cher
- Le référencement n'est PAS une histoire de technique, mais de communication et de bon sens !
Cette mini-formation s'adresse aux entrepreneurs qui ont un site ou un projet de site Internet.
Collaboraive sharing of molecules and data in the mobile ageSean Ekins
An overview of using collaborative software in small and large scale collaborations in drug discovery. A focus on Tuberculosis. Also analysis of collaboration and mobile apps for science
CDD: Vault, CDD: Vision and CDD: Models software for biologists and chemists ...Sean Ekins
A perspective on 12 yrs of CDD and developing products and collaborations.
A presentation given at the ACS meeting in San Diego - small business section
A potential vision of the future "the ncecessary", developed for a presentation at to be provocative. The goal was to think about the near and far future and put it into context with some of the science happening now as well as disruptive steps happening in rare disease science funding. Several slides highlight 'the ideal situation'.
Ensuring Chemical Structure, Biological Data and Computational Model Quality
A talk given at SLAS 2016 mon Jan 25th in San Diego
covers published work and recent forays with BIA 10-2474
Le web sémantique pour mieux anticiper le futurSylvain Gateau
Après le web 1.0 et le web 2.0, place au web sémantique. Jusque là encore unilatérale, la relation homme / machine prend une nouvelle dimension avec la sémantisation des contenus : les machines sont désormais capables de comprendre et d’exploiter le contenu. Pour notre plus grand bien ?
Le web sémantique est en marche pour nous préparer au futur. Des courants de pensées, tels que le « Future friendly web », prônent un web propre, structuré, et véhiculant du contenu porteur de sens, prêt à s’adapter et à être diffusé n’importe où, n’importe quand. À la croisée des Sciences Sociales et Humaines et des Sciences de l’Information et de la Communication, le web sémantique est donc sur le point de redéfinir nos relations communicationnelles ainsi que l’organisation de l’écosystème numérique.
Vers de nouveaux métiers ? De nouveaux acteurs ? De nouvelles pratiques ? Une chose est sûre, c’est qu’à partir d’aujourd’hui, la machine entre un peu plus dans notre sphère intime, relationnelle et communicationnelle. Un pas de plus vers l’intelligence artificielle ?
Conférence "Optimiser son référencement Internet"Sylvie de Meeûs
- Le référencement naturel est (toujours !) le meilleur moyen d'attirer de nouveaux clients
- Le référencement ne coûte pas cher
- Le référencement n'est PAS une histoire de technique, mais de communication et de bon sens !
Cette mini-formation s'adresse aux entrepreneurs qui ont un site ou un projet de site Internet.
Collaboraive sharing of molecules and data in the mobile ageSean Ekins
An overview of using collaborative software in small and large scale collaborations in drug discovery. A focus on Tuberculosis. Also analysis of collaboration and mobile apps for science
BIOBASE, the leader in data annotation and curation for genomics, took part in the Genome Informatics Alliance 2012: Logistics meeting in Oregon, and had an opportunity to present on trends in annotation of genomic data.
Beating Bugs with Big Data: Harnessing HPC to Realize the Potential of Genomi...Tom Connor
Introducing the HPC challenges associated with developing a set of clinical microbial genomics services in the NHS in Wales. Demonstrating the potential of these technologies, and the impact it is already having for the patients of the Welsh NHS.
The current paradigm in the pharmaceutical industry is that products can only be created and developed by massive collaborative teams. Each company has to build their own costly R&D platforms and IT infrastructure. Other research industries realized decades ago that they had to share data and methods because of cost. The pharmaceutical industry has been slow to realize this. Expanding beyond our recent book (Collaborative Computational Technologies for Biomedical Research) in which a growing number of technologies, consortia, precompetitive initiatives and complex collaboration networks are described, we suggest a more open drug discovery is being enabled by collaborative computational technologies. Academia however, is not training the next generation of scientists to practice open science or even collaborate, this represents challenges and opportunities. We will describe our observations and make recommendations that impact everyone from technology developers to granting agencies. This may enable future discoveries to be made outside traditional institutions.
E.Gombocz: Semantics in a Box (SemTech 2013-04-30)Erich Gombocz
Semantic W3C standards provide a framework for the creation of knowledge bases that are extensible, coherent, interoperable, and on which interactive analytics systems can be developed. A growing number of knowledge bases are being built on these standards— in particular as Linked Open Data (LOD) resources, and their availability has received increasing attention in industry and academia. Using LOD resources to provide value to industry is challenging, however, and early expectations have not always been met: issues arise from the alignment of public and experimental corporate standards, from inconsistent URI policies, and from the use of internal, non-formal application ontologies. To add to this, often the reliability of resources is problematic, from service levels to SPARQL endpoint uptime to URI persistence. Not the least, in many cases provenance issues have not properly resolved, and there are serious funding concerns related to government grant-backed resources. For this reasons, an integrated data appliance (iDA) preloaded with semantically integrated public knowledgebases provides an enterprise-ready “Semantics In-a-box” solution to address those shortcomings effectively.
A talk given at the International Congress "Contrasts in Pharmacology 2.0" held in Turin, May 14-16 2015
It describes our work with Bigger datasets, working on Tuberculosis as well as other areas.
Similar to Acs talk data intensive drug design v2 (20)
Presentation from AAPS PharmSci360 (October 23, 2023) in which I describe highlights of my Springer/AAPS book Winning Grants (https://link.springer.com/book/10.1007/978-3-031-27516-6) - presenting a 'how to' guide on writing small business grants - e.g. NIH STTR and SBIR grants. Written by someone experienced in winning such grants.
Evaluating Multiple Machine Learning Models for Biodegradation and Aquatic To...Sean Ekins
The presentation was given at SETAC 2022 Nov 16 and describes our work on Evaluating Multiple Machine Learning Models for Biodegradation and Aquatic Toxicity.
We generated many models that are available to license in our MegaTox software. We found that the support vector machines performed the best after assessing many algorithms for both classification and regression models.
The authors of this work are Thomas R Lane, Fabio Urbina and Sean Ekins.
The contact is sean@collaborationspharma.com
A presentation at the Global Genes rare drug development symposium on governm...Sean Ekins
This presentation from June 12 2020 gives a brief overview of my experience of 15 years of applying for government grants to fund small companies. Prior to this I had no experience of applying for such grants. The bottom line for rare disease groups / families is find a scientist that can do this or assist you. please also see www.collaborationspharma.com
Leveraging Science Communication and Social Media to Build Your Brand and Ele...Sean Ekins
Slides from AAPS Careers session by Maren Katherina Preis, Kyle Bagin, Sean Ekins
Provides some clear steps on how you could use social media to help your career.
Oral presentation given in MEDI session at 2017 ACS in DC.
co-authors Kimberley M. Zorn, Mary A. Lingerfelt, Jair L. de Siqueira-Neto, Alex M. Clark, Sean Ekins
describes drug repurposing and machine learning - for more details see www.collaborationspharma.com
Assay Central: A New Approach to Compiling Big Data and Preparing Machine Lea...Sean Ekins
Oral presentation at 2017 ACS in DC - given by Kimberley Zorn
co-authors include Mary A. Lingerfelt, Alex M. Clark, Sean Ekins
for more details see www.collaborationspharma.com
Five Ways to Use Social Media to Raise Awareness for Your Paper or ResearchSean Ekins
Presentation given at the AAPS 2016 conference in Denver. Some of the slides are from AAPS, Some from Kudos and some from Figshare. One slide is from Tony Williams. All slides used with permission.
Pros and cons of social networking for scientistsSean Ekins
Over the past 4 years I have been using social networking tools for scientists more inspired by Antony Williams. I realized I am using many tools and there are pros and cons of them. Here is my brief summary.
CDD: Vault, CDD: Vision and CDD: Models for Drug Discovery CollaborationsSean Ekins
A talk given at SERMACS 7th Nov 2015 in Memphis, describes CDD Vault, CDD Vision and CDD Models. In addition it also describes how the software is used in large and smaller scale collaborations for drug discovery.
Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Mode...Sean Ekins
Slides from SERMACS 2015 meeting in Memphis 2015 describing a collaborative project with SRI International and Rutgers. The work was published in PLOS ONE http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141076
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Here is the updated list of Top Best Ayurvedic medicine for Gas and Indigestion and those are Gas-O-Go Syp for Dyspepsia | Lavizyme Syrup for Acidity | Yumzyme Hepatoprotective Capsules etc
Integrating Ayurveda into Parkinson’s Management: A Holistic ApproachAyurveda ForAll
Explore the benefits of combining Ayurveda with conventional Parkinson's treatments. Learn how a holistic approach can manage symptoms, enhance well-being, and balance body energies. Discover the steps to safely integrate Ayurvedic practices into your Parkinson’s care plan, including expert guidance on diet, herbal remedies, and lifestyle modifications.
DISSERTATION on NEW DRUG DISCOVERY AND DEVELOPMENT STAGES OF DRUG DISCOVERYNEHA GUPTA
The process of drug discovery and development is a complex and multi-step endeavor aimed at bringing new pharmaceutical drugs to market. It begins with identifying and validating a biological target, such as a protein, gene, or RNA, that is associated with a disease. This step involves understanding the target's role in the disease and confirming that modulating it can have therapeutic effects. The next stage, hit identification, employs high-throughput screening (HTS) and other methods to find compounds that interact with the target. Computational techniques may also be used to identify potential hits from large compound libraries.
Following hit identification, the hits are optimized to improve their efficacy, selectivity, and pharmacokinetic properties, resulting in lead compounds. These leads undergo further refinement to enhance their potency, reduce toxicity, and improve drug-like characteristics, creating drug candidates suitable for preclinical testing. In the preclinical development phase, drug candidates are tested in vitro (in cell cultures) and in vivo (in animal models) to evaluate their safety, efficacy, pharmacokinetics, and pharmacodynamics. Toxicology studies are conducted to assess potential risks.
Before clinical trials can begin, an Investigational New Drug (IND) application must be submitted to regulatory authorities. This application includes data from preclinical studies and plans for clinical trials. Clinical development involves human trials in three phases: Phase I tests the drug's safety and dosage in a small group of healthy volunteers, Phase II assesses the drug's efficacy and side effects in a larger group of patients with the target disease, and Phase III confirms the drug's efficacy and monitors adverse reactions in a large population, often compared to existing treatments.
After successful clinical trials, a New Drug Application (NDA) is submitted to regulatory authorities for approval, including all data from preclinical and clinical studies, as well as proposed labeling and manufacturing information. Regulatory authorities then review the NDA to ensure the drug is safe, effective, and of high quality, potentially requiring additional studies. Finally, after a drug is approved and marketed, it undergoes post-marketing surveillance, which includes continuous monitoring for long-term safety and effectiveness, pharmacovigilance, and reporting of any adverse effects.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path