This document discusses how the method used to dispense liquid samples, such as acoustic droplet ejection versus serial dilution tips, can profoundly impact biological, computational, and statistical analyses using that data. It summarizes research comparing data from 14 compounds dispensed using both acoustic droplet ejection and serial dilution tips, finding a poor correlation between the measured potency results from the two techniques. The document advocates that dispensing method be carefully considered and standardized to ensure quality data for building computational models or running analyses.
Dispensing processes profoundly influence estimates of biological activity of compounds. In this study using published inhibitor data for the tyrosine kinase EphB4, we show that IC50 values obtained via disposable tip-based serial dilution and dispensing versus acoustic dispensing differ by orders of magnitude with no correlation or ranking of datasets. Importantly, the computed EphB4 pharmacophores derived from this data differ for each dataset. Acoustic dispensing correctly highlights multiple hydrophobic features in the pharmacophore and correlates with calculated LogP values. Significantly, the acoustic dispensing-derived pharmacophore correctly identified active compounds in a test set. The subsequent analysis of crystal structures for other published EphB4 inhibitors and automated development of pharmacophores, indicated they were comparable to those developed with acoustic dispensing data. In short, dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research and in drug discovery.
Dispensing Processes Impact Computational and Statistical AnalysesSean Ekins
1) Dispensing processes like tip-based serial dilution vs acoustic dispensing can impact computational and statistical analyses due to differences in generated data quality.
2) Pharmacophore models of EphB4 inhibitors generated from data produced via acoustic dispensing showed better correlations and predictive power than models from tip-based data.
3) Automated pharmacophore generation from crystal structures was more similar to the model from acoustic data, highlighting the importance of hydrophobic features that were missing from the tip-based model. This suggests dispensing methods can influence computational analyses.
The study investigated the effect of nano-bio interfaces on the genotoxicity of titanium dioxide nanoparticles. It found that the medium which elicited the smallest nanoparticle agglomerates (KF medium containing serum proteins) was associated with the highest cellular uptake, micronuclei formation, and percentage of cells in the S phase of the cell cycle. In contrast, DNA damage occurred regardless of agglomeration or uptake. The results suggest that inhalation exposure may not cause chromosomal damage in lung cells, but ingestion exposing nanoparticles to serum proteins could lower agglomeration and induce micronuclei formation.
Sigma Xi Student Research Showcase Presentationrprasad5
1) The study evaluated the effect of nano-bio interfaces on the genotoxicity of titanium dioxide nanoparticles using different treatment media.
2) The medium that elicited the smallest nanoparticle agglomerates (KF medium containing serum proteins) was associated with the highest cellular uptake, micronuclei formation, and increased percentage of cells in the S phase of the cell cycle.
3) In contrast, DNA damage was induced regardless of agglomeration and cellular uptake. The results suggest that while inhalation exposure may not induce micronuclei in lung cells, ingestion exposing nanoparticles to serum proteins could lower agglomeration and induce micronuclei formation.
Dispensing processes profoundly influence estimates of biological activity of compounds. In this study using published inhibitor data for the tyrosine kinase EphB4, we show that IC50 values obtained via disposable tip-based serial dilution and dispensing versus acoustic dispensing differ by orders of magnitude with no correlation or ranking of datasets. Importantly, the computed EphB4 pharmacophores derived from this data differ for each dataset. Acoustic dispensing correctly highlights multiple hydrophobic features in the pharmacophore and correlates with calculated LogP values. Significantly, the acoustic dispensing-derived pharmacophore correctly identified active compounds in a test set. The subsequent analysis of crystal structures for other published EphB4 inhibitors and automated development of pharmacophores, indicated they were comparable to those developed with acoustic dispensing data. In short, dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research and in drug discovery.
Dispensing Processes Impact Computational and Statistical AnalysesSean Ekins
1) Dispensing processes like tip-based serial dilution vs acoustic dispensing can impact computational and statistical analyses due to differences in generated data quality.
2) Pharmacophore models of EphB4 inhibitors generated from data produced via acoustic dispensing showed better correlations and predictive power than models from tip-based data.
3) Automated pharmacophore generation from crystal structures was more similar to the model from acoustic data, highlighting the importance of hydrophobic features that were missing from the tip-based model. This suggests dispensing methods can influence computational analyses.
The study investigated the effect of nano-bio interfaces on the genotoxicity of titanium dioxide nanoparticles. It found that the medium which elicited the smallest nanoparticle agglomerates (KF medium containing serum proteins) was associated with the highest cellular uptake, micronuclei formation, and percentage of cells in the S phase of the cell cycle. In contrast, DNA damage occurred regardless of agglomeration or uptake. The results suggest that inhalation exposure may not cause chromosomal damage in lung cells, but ingestion exposing nanoparticles to serum proteins could lower agglomeration and induce micronuclei formation.
Sigma Xi Student Research Showcase Presentationrprasad5
1) The study evaluated the effect of nano-bio interfaces on the genotoxicity of titanium dioxide nanoparticles using different treatment media.
2) The medium that elicited the smallest nanoparticle agglomerates (KF medium containing serum proteins) was associated with the highest cellular uptake, micronuclei formation, and increased percentage of cells in the S phase of the cell cycle.
3) In contrast, DNA damage was induced regardless of agglomeration and cellular uptake. The results suggest that while inhalation exposure may not induce micronuclei in lung cells, ingestion exposing nanoparticles to serum proteins could lower agglomeration and induce micronuclei formation.
Controlling Brain Circuits With Light - Ed Boyden - H+ Summit @ HarvardHumanity Plus
Ed Boyden
Assistant Professor, MIT Media Lab, MIT Brain and Cognitive Sciences, and MIT Biological Engineering
Controlling Brain Circuits with Light
The brain is three-dimensional and densely-wired with billions of heterogeneous computational primitives. Understanding how these elements work in real time to mediate behavior and consciousness, and how they are compromised in neural pathology, is a top priority. We have recently revealed methods for real-time optical activation and silencing of specific cell types in the brain, using naturally-occurring molecular sensitizers such as channelrhodopsin-2, halorhodopsin, and archaerhodopsin. Building off of these molecular tools, we also have created optical hardware and algorithms for systematically testing the contribution of brain regions, cell types, and circuit connections to behavioral functions. We are also working on noninvasive methods of information delivery to the brain. We discuss the application of these technologies to the analysis of neural dynamics, as well as to translation for new treatments for human disease, and eventually towards augmentation of the human condition.
Ed Boyden is the Benesse Career Development Professor at the MIT Media Lab, assistant professor of Biological Engineering and Brain and Cognitive Sciences at MIT, and leader of the Synthetic Neurobiology Group. His group aims to discover principles for controlling neural circuits in order to understand how cognition and emotion arise, and also to enable systematic repair of intractable brain disorders such as epilepsy, Parkinson's disease, post-traumatic stress disorder, and chronic pain. In order to accomplish this, his group invents new tools for controlling and observing the computations performed by brain circuits. He has launched an award-winning series of classes at MIT that teach principles of neuroengineering, starting with basic principles of how to control and observe neural functions, and culminating with launching companies in the nascent neurotechnology space. He was named to the "Top 35 Innovators Under the Age of 35" by Technology Review in 2006, his lab's work was selected to the Discovery Science Channel's "Top 5 Best Science Moments" in 2007, and he was selected for the "Top 20 Brains Under Age 40" by Discover Magazine in 2008, as well as awarded the NIH Director's New Innovator Award and the Society for Neuroscience Research Award for Innovation in Neuroscience. Ed received his PhD in neurosciences from Stanford University as a Hertz Fellow, where he discovered that the molecular mechanisms used to store a memory are determined by the content to be learned. Before, he received three degrees in electrical engineering and physics from MIT. He has contributed to over 200 papers, current or pending patents, and articles, has given over 80 invited talks, and writes a column for Technology Review magazine.
This document contains an outline for an IB biology textbook. It includes 14 chapters that cover core biology topics like cells, genetics, and ecology, as well as optional chapters on subjects like human nutrition, physiology, and biotechnology. Each chapter begins with an introduction and then breaks down the topic into sections, with practice questions at the end. The document also includes additional sections offering advice for IB biology students on assessments.
AiChE National Meeting 2012 Pittsburgh Presentation Flow Continuousdominev
1) In-situ FTIR spectroscopy using a ReactIR flow cell allows for real-time monitoring and analysis of continuous chemical reactions without interrupting flow.
2) Case studies demonstrated its use in optimizing a continuous ozonolysis reaction for safer API production, achieving a 2.7kg yield in 4 days.
3) Rapid screening and optimization of a Doebner modification reaction was also demonstrated, identifying optimal conditions within hours using on-the-fly variation of temperature and residence time analyzed via the in-situ FTIR.
This document discusses theoretical explorations of protein liquid crystal electronic gels and their potential applications. It describes how bio-neural gel packs composed of synthetic cerebral neurons suspended in a protein liquid crystal electronic gel medium could function as organic computer circuits modeled after the human brain. The technology is assessed to be at a similar level to science fiction depictions from Star Trek and portends new phenomenal technologies and markets. Diagrams show the logic schema of how protein liquid crystal electronic gel packs could work.
This document summarizes a criticality benchmark analysis of water-reflected uranium oxyfluoride slabs. It outlines the experiment background, evaluation process, results of the uncertainty and bias analyses, sample calculations comparing results using different nuclear data libraries, and current efforts to revise the benchmark. The benchmark evaluation assesses the minimum critical thickness of an infinite slab based on experimental data from 1955-1956. It analyzes uncertainties in parameters and simplifications of the model to determine bias. The detailed model results are within uncertainties of the simplified model, validating its use. An updated benchmark will be presented to the ICSBEP working group in 2010.
This document discusses using in-line FTIR analytics to optimize continuous processes. It presents two case studies:
1) Developing a continuous ozonolysis process for an API intermediate using in-situ FTIR to monitor the reaction in real-time, allowing production of 2.7kg of product in 2 weeks.
2) Optimizing a Doebner modification of the Knoevenagel reaction in continuous mode using in-line FTIR to visually monitor the reaction and screen conditions.
In both cases, in-line FTIR provided real-time analysis of the reaction and intermediates, enabling rapid process development and optimization without the need for offline sampling and analysis. This
The document introduces the InBody body composition analyzer company. It discusses the company's dedication to body composition analysis, its recognition as the top brand, and ownership of patents and approvals from regulatory bodies. The company pioneered the overseas market and has over 30 distributors worldwide. It also has a stable financial structure with continuous sales and profit growth.
The document summarizes research on mechanical loading of rigid intramuscular implants. It describes clinical trials of BION implants which use microstimulators to stimulate muscles. It was found that some implants fractured after long-term intense exercise. Testing showed the glass capsule could fail due to repetitive stress. The design was reengineered to fuse components together and withstand over 4 million cycles of loading without failure.
Qualifications And Experience PresentationKevin Baker
The document discusses the author's background and accomplishments in physics and optical coherence tomography (OCT). It then summarizes the author's work developing algorithms to analyze OCT signals and images for non-invasive glucose monitoring. Key contributions included preprocessing algorithms to reduce noise, aggregating 3D OCT images into 1D signals, and using multivariate statistics to understand trends in the data and identify outliers. The goal was to optimize the system performance and mitigate sources of error like motion artifacts.
This document discusses molecular design for drug discovery. It outlines how molecular design can be used to control compound behavior through manipulation of molecular properties. Hypothesis-driven and prediction-driven approaches to molecular design are discussed. Relationship between structures, such as bioisosterism, are important for analyzing biological activity and physicochemical properties. Library design for screening is also covered, focusing on diversity, coverage, and neighborhood sampling of chemical space.
Exosomes: Exploiting the Diagnostic and Therapeutic Potential of Nature’s Bio...HORIBA Particle
Research on exosomes and other forms of extracellular vesicles (EVs) have rapidly expanded over the last two decades. These lipid-enclosed, nanoscale messengers are released from cells packed with diverse cargo and can travel long distances to modify the function of target cells. Found in abundant quantities in biological fluids like blood, there is great clinical interest in using EVs as diagnostic markers or altering their properties for therapeutic delivery. Tune in to find out more about what exosomes are, how researchers study them, and what challenges remain. This talk will highlight multi-laser nanoparticle tracking analysis (NTA) with the ViewSizer 3000 and what it offers in exosome research.
View recorded webinars:
http://bit.ly/particlewebinars
The document discusses synthetic biology and its potential applications. It explains foundational concepts like DNA, mRNA and proteins. It describes how DNA parts can be standardized and assembled to program bacteria. Examples are given of applications like biochemical sensors, genetic oscillators, and biological computation. The document conveys that synthetic biology makes biotechnology more accessible and could impact areas like healthcare, energy and education. It promotes synthetic biology as an exciting field that enables problem-based learning.
Getting the Big Picture by Joining up the SAR dotsSorel Muresan
Getting the Big Picture by Joining up the SAR dots
This document discusses challenges in integrating structure and bioactivity data at large scales due to the volume and complexity of unstructured data from various sources. It describes efforts to extract chemical entities from text using natural language processing and to standardize structures. The Chemistry Connect knowledge base aims to enable searching across internal and external datasets by developing a chemical dictionary and common representation of concepts.
Detection of Kidney Stone using Neural Network ClassifierIRJET Journal
This document summarizes a research paper that proposes using neural networks to detect kidney stones from CT scan images. The researchers aim to improve detection accuracy by using discrete wavelet transforms to extract features from the images, as well as a gray-level co-occurrence matrix and watershed algorithm. They train neural networks on sample CT images that have been diagnosed for kidney stones. The proposed method is meant to provide automatic, accurate detection of kidney stones to help with diagnosis and treatment.
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
Learning Clusters in Autism Spectrum Disorder: Image-Based Clustering of Eye-...Mahmoud Elbattah
Presented at Presented at 41st Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
https://ieeexplore.ieee.org/document/8856904
Authors:
Mahmoud Elbattah, Romuald Carette, Gilles Dequen, Jean-Luc Guérin, Federica Cilia
Université de Picardie Jules Verne, France
mahmoud.elbattah@u-picardie.fr
Enhancing high throughput screeing for mycobacterium tuberculosis drug discov...Sean Ekins
This document summarizes research applying Bayesian machine learning models to enhance high-throughput screening for drug discovery against Mycobacterium tuberculosis (Mtb). The researchers built Bayesian classification models using over 200,000 compounds and their bioactivity data against Mtb. They tested the models on new screening data, achieving hit rates 4-10 times higher than random. The models were also used to prospectively select compounds for screening from large libraries, identifying several novel potent lead series. This work demonstrates that computational models can efficiently prioritize compounds for screening to increase hit discovery for Mtb drug development.
Tracking Trends in Korean Information Science Research, 2000-2011SoYoung YU
This is a presentation file of "Tracking Trends in Korean Information Science Research, 2000-2011" which was published in COLLNET 2012 proceeding, October 23rd, 2012.
If you need a full paper of it, feel free to contact So Young Yu (soyoung.yu21@gmail.com)
The Computational Microscope Images Biomolecular Machines and Nanodevices - K...TCBG
The document describes using molecular dynamics simulations with the NAMD software and supercomputers to act as a "computational microscope" for inspecting biomolecular machines and nanodevices at the atomic level. It provides examples of simulating protein folding, studying the mechanical strength of blood clots, and improving the design of a kinase sensor by revealing problems and informing new designs through simulations.
Unsupervised Deconvolution Neural Network for High Quality Ultrasound ImagingShujaat Khan
High quality US imaging demand large number of measurements that can increase the cost, size and power requirements. Therefore, low-powered, portable and 3D ultrasound imaging system require reconstruction algorithms that can produce high quality images using fewer receive measurements. Number of model specific methods has been proposed which doesn't work under perturbation. For instance, compressive deconvolution ultrasound which provide a reasonable quality with limited measurements however, it has its own down-sides such as high computation cost and accurate estimation of point spread function (PSF). An other major limitation of conventional methods is that they require RF or base-band signal which is difficult to obtain from portable US systems. To deal with the aforementioned issues, in this study we designed a novel deep deconvolution model for image domain-based deconvolution. The proposed deep deconvolution (DeepDeconv) model can be trained in an unsupervised fashion, alleviate the need of paired high and low quality images. The model was evaluated on both the phantom and in-vivo scans for various sampling configurations. The proposed DeepDeconv significantly enhance the details of anatomical structures and using unsupervised learning on average it achieved 2.14dB, 4.96dB and 0.01 units gain in CR, PSNR and SSIM values respectively, which are comparable to the supervised method.
Controlling Brain Circuits With Light - Ed Boyden - H+ Summit @ HarvardHumanity Plus
Ed Boyden
Assistant Professor, MIT Media Lab, MIT Brain and Cognitive Sciences, and MIT Biological Engineering
Controlling Brain Circuits with Light
The brain is three-dimensional and densely-wired with billions of heterogeneous computational primitives. Understanding how these elements work in real time to mediate behavior and consciousness, and how they are compromised in neural pathology, is a top priority. We have recently revealed methods for real-time optical activation and silencing of specific cell types in the brain, using naturally-occurring molecular sensitizers such as channelrhodopsin-2, halorhodopsin, and archaerhodopsin. Building off of these molecular tools, we also have created optical hardware and algorithms for systematically testing the contribution of brain regions, cell types, and circuit connections to behavioral functions. We are also working on noninvasive methods of information delivery to the brain. We discuss the application of these technologies to the analysis of neural dynamics, as well as to translation for new treatments for human disease, and eventually towards augmentation of the human condition.
Ed Boyden is the Benesse Career Development Professor at the MIT Media Lab, assistant professor of Biological Engineering and Brain and Cognitive Sciences at MIT, and leader of the Synthetic Neurobiology Group. His group aims to discover principles for controlling neural circuits in order to understand how cognition and emotion arise, and also to enable systematic repair of intractable brain disorders such as epilepsy, Parkinson's disease, post-traumatic stress disorder, and chronic pain. In order to accomplish this, his group invents new tools for controlling and observing the computations performed by brain circuits. He has launched an award-winning series of classes at MIT that teach principles of neuroengineering, starting with basic principles of how to control and observe neural functions, and culminating with launching companies in the nascent neurotechnology space. He was named to the "Top 35 Innovators Under the Age of 35" by Technology Review in 2006, his lab's work was selected to the Discovery Science Channel's "Top 5 Best Science Moments" in 2007, and he was selected for the "Top 20 Brains Under Age 40" by Discover Magazine in 2008, as well as awarded the NIH Director's New Innovator Award and the Society for Neuroscience Research Award for Innovation in Neuroscience. Ed received his PhD in neurosciences from Stanford University as a Hertz Fellow, where he discovered that the molecular mechanisms used to store a memory are determined by the content to be learned. Before, he received three degrees in electrical engineering and physics from MIT. He has contributed to over 200 papers, current or pending patents, and articles, has given over 80 invited talks, and writes a column for Technology Review magazine.
This document contains an outline for an IB biology textbook. It includes 14 chapters that cover core biology topics like cells, genetics, and ecology, as well as optional chapters on subjects like human nutrition, physiology, and biotechnology. Each chapter begins with an introduction and then breaks down the topic into sections, with practice questions at the end. The document also includes additional sections offering advice for IB biology students on assessments.
AiChE National Meeting 2012 Pittsburgh Presentation Flow Continuousdominev
1) In-situ FTIR spectroscopy using a ReactIR flow cell allows for real-time monitoring and analysis of continuous chemical reactions without interrupting flow.
2) Case studies demonstrated its use in optimizing a continuous ozonolysis reaction for safer API production, achieving a 2.7kg yield in 4 days.
3) Rapid screening and optimization of a Doebner modification reaction was also demonstrated, identifying optimal conditions within hours using on-the-fly variation of temperature and residence time analyzed via the in-situ FTIR.
This document discusses theoretical explorations of protein liquid crystal electronic gels and their potential applications. It describes how bio-neural gel packs composed of synthetic cerebral neurons suspended in a protein liquid crystal electronic gel medium could function as organic computer circuits modeled after the human brain. The technology is assessed to be at a similar level to science fiction depictions from Star Trek and portends new phenomenal technologies and markets. Diagrams show the logic schema of how protein liquid crystal electronic gel packs could work.
This document summarizes a criticality benchmark analysis of water-reflected uranium oxyfluoride slabs. It outlines the experiment background, evaluation process, results of the uncertainty and bias analyses, sample calculations comparing results using different nuclear data libraries, and current efforts to revise the benchmark. The benchmark evaluation assesses the minimum critical thickness of an infinite slab based on experimental data from 1955-1956. It analyzes uncertainties in parameters and simplifications of the model to determine bias. The detailed model results are within uncertainties of the simplified model, validating its use. An updated benchmark will be presented to the ICSBEP working group in 2010.
This document discusses using in-line FTIR analytics to optimize continuous processes. It presents two case studies:
1) Developing a continuous ozonolysis process for an API intermediate using in-situ FTIR to monitor the reaction in real-time, allowing production of 2.7kg of product in 2 weeks.
2) Optimizing a Doebner modification of the Knoevenagel reaction in continuous mode using in-line FTIR to visually monitor the reaction and screen conditions.
In both cases, in-line FTIR provided real-time analysis of the reaction and intermediates, enabling rapid process development and optimization without the need for offline sampling and analysis. This
The document introduces the InBody body composition analyzer company. It discusses the company's dedication to body composition analysis, its recognition as the top brand, and ownership of patents and approvals from regulatory bodies. The company pioneered the overseas market and has over 30 distributors worldwide. It also has a stable financial structure with continuous sales and profit growth.
The document summarizes research on mechanical loading of rigid intramuscular implants. It describes clinical trials of BION implants which use microstimulators to stimulate muscles. It was found that some implants fractured after long-term intense exercise. Testing showed the glass capsule could fail due to repetitive stress. The design was reengineered to fuse components together and withstand over 4 million cycles of loading without failure.
Qualifications And Experience PresentationKevin Baker
The document discusses the author's background and accomplishments in physics and optical coherence tomography (OCT). It then summarizes the author's work developing algorithms to analyze OCT signals and images for non-invasive glucose monitoring. Key contributions included preprocessing algorithms to reduce noise, aggregating 3D OCT images into 1D signals, and using multivariate statistics to understand trends in the data and identify outliers. The goal was to optimize the system performance and mitigate sources of error like motion artifacts.
This document discusses molecular design for drug discovery. It outlines how molecular design can be used to control compound behavior through manipulation of molecular properties. Hypothesis-driven and prediction-driven approaches to molecular design are discussed. Relationship between structures, such as bioisosterism, are important for analyzing biological activity and physicochemical properties. Library design for screening is also covered, focusing on diversity, coverage, and neighborhood sampling of chemical space.
Exosomes: Exploiting the Diagnostic and Therapeutic Potential of Nature’s Bio...HORIBA Particle
Research on exosomes and other forms of extracellular vesicles (EVs) have rapidly expanded over the last two decades. These lipid-enclosed, nanoscale messengers are released from cells packed with diverse cargo and can travel long distances to modify the function of target cells. Found in abundant quantities in biological fluids like blood, there is great clinical interest in using EVs as diagnostic markers or altering their properties for therapeutic delivery. Tune in to find out more about what exosomes are, how researchers study them, and what challenges remain. This talk will highlight multi-laser nanoparticle tracking analysis (NTA) with the ViewSizer 3000 and what it offers in exosome research.
View recorded webinars:
http://bit.ly/particlewebinars
The document discusses synthetic biology and its potential applications. It explains foundational concepts like DNA, mRNA and proteins. It describes how DNA parts can be standardized and assembled to program bacteria. Examples are given of applications like biochemical sensors, genetic oscillators, and biological computation. The document conveys that synthetic biology makes biotechnology more accessible and could impact areas like healthcare, energy and education. It promotes synthetic biology as an exciting field that enables problem-based learning.
Getting the Big Picture by Joining up the SAR dotsSorel Muresan
Getting the Big Picture by Joining up the SAR dots
This document discusses challenges in integrating structure and bioactivity data at large scales due to the volume and complexity of unstructured data from various sources. It describes efforts to extract chemical entities from text using natural language processing and to standardize structures. The Chemistry Connect knowledge base aims to enable searching across internal and external datasets by developing a chemical dictionary and common representation of concepts.
Detection of Kidney Stone using Neural Network ClassifierIRJET Journal
This document summarizes a research paper that proposes using neural networks to detect kidney stones from CT scan images. The researchers aim to improve detection accuracy by using discrete wavelet transforms to extract features from the images, as well as a gray-level co-occurrence matrix and watershed algorithm. They train neural networks on sample CT images that have been diagnosed for kidney stones. The proposed method is meant to provide automatic, accurate detection of kidney stones to help with diagnosis and treatment.
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
Learning Clusters in Autism Spectrum Disorder: Image-Based Clustering of Eye-...Mahmoud Elbattah
Presented at Presented at 41st Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
https://ieeexplore.ieee.org/document/8856904
Authors:
Mahmoud Elbattah, Romuald Carette, Gilles Dequen, Jean-Luc Guérin, Federica Cilia
Université de Picardie Jules Verne, France
mahmoud.elbattah@u-picardie.fr
Enhancing high throughput screeing for mycobacterium tuberculosis drug discov...Sean Ekins
This document summarizes research applying Bayesian machine learning models to enhance high-throughput screening for drug discovery against Mycobacterium tuberculosis (Mtb). The researchers built Bayesian classification models using over 200,000 compounds and their bioactivity data against Mtb. They tested the models on new screening data, achieving hit rates 4-10 times higher than random. The models were also used to prospectively select compounds for screening from large libraries, identifying several novel potent lead series. This work demonstrates that computational models can efficiently prioritize compounds for screening to increase hit discovery for Mtb drug development.
Tracking Trends in Korean Information Science Research, 2000-2011SoYoung YU
This is a presentation file of "Tracking Trends in Korean Information Science Research, 2000-2011" which was published in COLLNET 2012 proceeding, October 23rd, 2012.
If you need a full paper of it, feel free to contact So Young Yu (soyoung.yu21@gmail.com)
The Computational Microscope Images Biomolecular Machines and Nanodevices - K...TCBG
The document describes using molecular dynamics simulations with the NAMD software and supercomputers to act as a "computational microscope" for inspecting biomolecular machines and nanodevices at the atomic level. It provides examples of simulating protein folding, studying the mechanical strength of blood clots, and improving the design of a kinase sensor by revealing problems and informing new designs through simulations.
Unsupervised Deconvolution Neural Network for High Quality Ultrasound ImagingShujaat Khan
High quality US imaging demand large number of measurements that can increase the cost, size and power requirements. Therefore, low-powered, portable and 3D ultrasound imaging system require reconstruction algorithms that can produce high quality images using fewer receive measurements. Number of model specific methods has been proposed which doesn't work under perturbation. For instance, compressive deconvolution ultrasound which provide a reasonable quality with limited measurements however, it has its own down-sides such as high computation cost and accurate estimation of point spread function (PSF). An other major limitation of conventional methods is that they require RF or base-band signal which is difficult to obtain from portable US systems. To deal with the aforementioned issues, in this study we designed a novel deep deconvolution model for image domain-based deconvolution. The proposed deep deconvolution (DeepDeconv) model can be trained in an unsupervised fashion, alleviate the need of paired high and low quality images. The model was evaluated on both the phantom and in-vivo scans for various sampling configurations. The proposed DeepDeconv significantly enhance the details of anatomical structures and using unsupervised learning on average it achieved 2.14dB, 4.96dB and 0.01 units gain in CR, PSNR and SSIM values respectively, which are comparable to the supervised method.
Impact of detector thickness on imaging characteristics of the Siemens Biogra...Anax Fotopoulos
This document summarizes a Monte Carlo study using GATE simulation of a Siemens Biograph DUO PET/CT scanner. It investigates the impact of detector thickness on imaging characteristics by simulating the scanner with LSO detectors of 2cm and 3cm thickness. The results show that increasing thickness from 2cm to 3cm improves detection efficiency, resulting in a sharper energy peak at 511 keV, higher counts, and better energy resolution and signal-to-noise ratio. However, thicker detectors may also delay signal processing and increase device cost and complexity.
This document discusses lensfree microscopy and tomography techniques developed by Serhan Isikman for biomedical applications. [1] Lensfree microscopy uses holograms recorded by a sensor array to digitally reconstruct microscope images over a wide field of view in a compact, low-cost system. [2] It has been used to rapidly count red blood cells on a chip with high accuracy. [3] Lensfree optical tomography similarly uses holograms from multiple angles to computationally generate 3D images without lenses, achieving micrometer-scale resolution.
Spotfire is used across many departments in Amgen Research, including high throughput screening, research informatics, therapeutic areas, and more. It allows for interactive data exploration through visualizations, zooming, and linking multiple data sources. The Spotfire Cockpit provides guided workflows and visualizations for tasks like exploring compound data in lead discovery and toxicology. Amgen is also interested in ontologies to represent relationships between targets, diseases, anatomy, and more to aid in data exploration and knowledge discovery.
The document provides an overview of an experimental project studying the motor protein kinesin using various single molecule techniques like optical tweezers and magnetic tweezers. The project is investigating the effects of heavy water (D2O) on kinesin-driven microtubule motility using gliding motility assays. Preliminary results show that microtubules are more stable in D2O, remaining active for over 24 hours compared to regular assays. Velocity measurements of microtubule movement are also being conducted. Future work will explore isotope effects using 18-oxygen water and the effects of osmotic stress on motility. The project involves collaborations between the documenting lab and other groups studying modeling and applications.
Nanoparticles are collections of atoms that bridge the classical and quantum worlds. They have high surface area to volume ratios and are only a few nanometers in size. The document discusses using computer simulations to model cadmium sulfide (CdS) nanoparticles and compare their properties to bulk CdS structures. The simulations use density functional theory to calculate electronic properties and molecular dynamics to simulate particle behavior over time.
Similar to Acs dispensing processes profoundly impact biological assays, computational and statistical analyses (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
This document outlines a presentation about leveraging social media to build a personal brand and career as a scientist. The presentation discusses comparing different social media platforms and how to use them effectively as a scientist. It also provides a "5 minute-a-week social scientist framework" for positioning yourself and your science online. Several speakers share their experiences using social media for their research and discuss generating interest in topics, deciding on an authentic personal brand, and cultural differences in social media use.
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.
academic / small company collaborations for rare and neglected diseasesv2Sean Ekins
This document discusses academic and small company collaborations for rare and neglected diseases. It provides background on rare diseases, noting they affect 6-7% of the population in the US and less than 1 in 2000 people in Europe. Many rare diseases have a genetic origin. The document then focuses on specific rare diseases, including Sanfilippo Syndrome, a lysosomal storage disorder caused by deficiencies in certain enzymes. Potential treatment approaches for Sanfilippo Syndrome are discussed such as enzyme replacement therapy, gene therapy, and substrate reduction therapy. The document also discusses machine learning models to identify potential drug candidates for other rare and neglected tropical diseases such as tuberculosis, Chagas disease, and Ebola virus.
This case study demonstrates how to build a machine learning model using kinase data from the CDD Public dataset and store it in a CDD Vault. Key steps include selecting active molecules from the kinase data, building a model, generating predictions for approved drugs in the vault using the model, and exporting the model. Models built in CDD can be used to score libraries, accessed by other groups, and exported to use in other software or mobile apps. The overall goal is to enable sharing of models between organizations and leverage both public and private models for drug discovery projects.
This case study demonstrates how to build a machine learning model using data from the Collaborative Drug Discovery (CDD) Public vault and apply the model to score compounds in a private CDD vault. Specifically, it shows how to:
1. Select active compounds from AZ-ChEMBL data in the public vault to train a model.
2. Build a model using the selected active compounds.
3. Generate predictions for approved drugs in a private vault using the new model.
4. Export the model for use in other software or share it with collaborators.
The goal is to illustrate how models can be developed in CDD and leveraged across projects and groups to help drug discovery
CDD: Vault, CDD: Vision and CDD: Models software for biologists and chemists ...Sean Ekins
CDD provides an integrated software suite for drug discovery called CDD Vault. It includes capabilities for data visualization, calculations, machine learning models, and collaborative workspaces. CDD Vault securely hosts large compound and data sets. Recent updates include advanced modeling and visualization tools. CDD is used widely in academia and industry and has over a decade of experience in facilitating drug discovery collaborations, including projects focused on neglected diseases.
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.
Pros and cons of social networking for scientistsSean Ekins
This document discusses Sean Ekins' experience using various online tools and platforms to increase the visibility of his scientific work and facilitate collaboration. It notes that Ekins uses multiple networks, tools and audiences due to working in different areas like drug discovery, grant writing and blogging. The document provides advice on using tools to connect with others, share your work in accessible formats, and assess the impact of your research. It discusses both the benefits and challenges of using these tools, including the ongoing effort needed to maintain an online presence.
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.
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
Rasamanikya is a excellent preparation in the field of Rasashastra, it is used in various Kushtha Roga, Shwasa, Vicharchika, Bhagandara, Vatarakta, and Phiranga Roga. In this article Preparation& Comparative analytical profile for both Formulationon i.e Rasamanikya prepared by Kushmanda swarasa & Churnodhaka Shodita Haratala. The study aims to provide insights into the comparative efficacy and analytical aspects of these formulations for enhanced therapeutic outcomes.
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
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
share - Lions, tigers, AI and health misinformation, oh my!.pptxTina Purnat
• Pitfalls and pivots needed to use AI effectively in public health
• Evidence-based strategies to address health misinformation effectively
• Building trust with communities online and offline
• Equipping health professionals to address questions, concerns and health misinformation
• Assessing risk and mitigating harm from adverse health narratives in communities, health workforce and health system
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
- Video recording of this lecture in English language: https://youtu.be/kqbnxVAZs-0
- Video recording of this lecture in Arabic language: https://youtu.be/SINlygW1Mpc
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Adhd Medication Shortage Uk - trinexpharmacy.comreignlana06
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1. Dispensing Processes Profoundly Impact
Biological, Computational and Statistical Analyses
Sean Ekins1, Joe Olechno2 Antony J. Williams3
1 Collaborationsin Chemistry, Fuquay Varina, NC.
2 Labcyte Inc, Sunnyvale, CA.
3 Royal Society of Chemistry, Wake Forest, NC.
Disclaimer: SE and AJW have no affiliation with Labcyte and have
not been engaged as consultants
2. Where do scientists get
chemistry/ biology
data?
Databases
Patents
Papers
Your own lab
Collaborators
“If I have seen further Some or all of the
than others, it is by above?
standing upon the What is common to
shoulders of giants.” all? – quality issues
Isaac Newton
3. ..drug structure quality is
Data can be found – but …
important
More groups doing in silico
repositioning
Target-based or ligand-based
Network and systems biology
integrating or using sets of
FDA drugs..if the structures
are incorrect predictions will
be too..
Need a definitive set of FDA
approved drugs with correct
structures
Also linkage between in vitro
data & clinical data
4. Structure Quality Issues
Database released and within days 100’s of errors found in structures
Science Translational Medicine 2011
NPC Browser http://tripod.nih.gov/npc/
DDT 17: 685-701 (2012)
DDT, 16: 747-750 (2011)
5. Its not just structure quality we
DDT editorial Dec 2011 need to worry about
This editorial led to the current
work http://goo.gl/dIqhU
6. Finding structures of Pharma molecules is hard
NCATS and MRC
made molecule
identifiers from
pharmas available
with no structures Southan et al., DDT, 18: 58-70 (2013)
7. How do you move Plastic leaching
a liquid?
McDonald et al., Science 2008,
322, 917.
Belaiche et al., Clin Chem 2009,
Images courtesy of Bing, Tecan 55, 1883-1884
8. Moving Liquids with sound: Acoustic Droplet Ejection (ADE)
Acoustic energy expels droplets without physical contact
Extremely precise
15.0
12.5
Extremely accurate 10.0
Rapid %CV 7.5
Auto-calibrating 5.0
Completely 2.5
touchless 0
0.1 1 10 100 1000 10000
Volume (nL)
No cross- Comley J, Nanolitre Dispensing, Drug Discovery World,
Summer 2004, 43-54
contamination
No leachates
No binding
8
Images courtesy of Labcyte Inc. http://goo.gl/K0Fjz
9. Using literature data from different dispensing methods to generate
computational models
Few molecule structures and corresponding datasets are public
Using data from 2 AstraZeneca patents –
Tyrosine kinase EphB4 pharmacophores (Accelrys Discovery
Studio) were developed using data for 14 compounds
IC50 determined using different dispensing methods
Analyzed correlation with simple descriptors (SAS JMP)
Calculated LogP correlation with log IC50 data for acoustic
dispensing (r2 = 0.34, p < 0.05, N = 14)
Barlaam, B. C.; Ducray, R., WO 2009/010794 A1, 2009
Barlaam, B. C.; Ducray, R.; Kettle, J. G., US 7,718,653 B2, 2010
11. A graph of the log IC50 values for tip-based serial dilution
and dispensing versus acoustic dispensing with direct dilution
shows a poor correlation between techniques (R2 = 0.246).
1.5
1
0.5
0
-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5
log IC50-tips
-0.5
-1
-1.5 acoustic
technique
-2 always gave
a more
-2.5
potent IC50
-3 value
log IC50-acoustic
12. Experimental Process
Results
Acoustic Acoustic Acoustic
Model Model Model
Generate Test models Test models against
14 Structures
pharmacophore models against new X-ray crystal structure
with Data
for EphB4 receptor data pharmacophores
Tip-based Tip-based Tip-based
Model Model Model
Results
Initial data set of 14 Independent data set of 12 Independent crystallography data
WO2009/010794, US 7,718,653 WO2008/132505 Bioorg Med Chem Lett 18:2776;
12
18:5717; 20:6242; 21:2207
13. Tyrosine kinase EphB4 Pharmacophores
Generated with Discovery
Studio (Accelrys)
Cyan = hydrophobic
Green = hydrogen bond
acceptor
Purple = hydrogen bond donor
Each model shows most
potent molecule mapping
Acoustic Tip based
Hydrophobic Hydrogen Hydrogen Observed vs.
features (HPF) bond acceptor bond donor predicted IC50
(HBA) (HBD) r
Acoustic mediated process
2 1 1 0.92
Tip-based process
0 2 1 0.80
• Ekins et al., PLOSONE, In press
14. Test set evaluation of pharmacophores
• An additional 12 compounds from AstraZeneca
Barlaam, B. C.; Ducray, R., WO 2008/132505 A1, 2008
• 10 of these compounds had data for tip based dispensing
and 2 for acoustic dispensing
• Calculated LogP and logD showed low but statistically
significant correlations with tip based dispensing (r2=
0.39 p < 0.05 and 0.24 p < 0.05, N = 36)
• Used as a test set for pharmacophores
• The two compounds analyzed with acoustic liquid
handling were predicted in the top 3 using the ‘acoustic’
pharmacophore
• The ‘Tip-based’ pharmacophore failed to rank the
retrieved compounds correctly
15. Automated receptor-ligand pharmacophore generation
method
Pharmacophores for the tyrosine kinase EphB4 generated from crystal
structures in the protein data bank PDB using Discovery Studio version 3.5.5
Cyan =
hydrophobic
Green = hydrogen
bond acceptor
Purple = hydrogen
bond donor
Grey = excluded
volumes
Each model shows
most potent
molecule mapping
Bioorg Med Chem Lett
2010, 20, 6242-6245.
Bioorg Med Chem Lett
2008, 18, 5717-5721.
Bioorg Med Chem Lett
2008, 18, 2776-2780.
Bioorg Med Chem Lett
2011, 21, 2207-2211.
16. Summary
• In the absence of structural data, pharmacophores and other
computational and statistical models are used to guide medicinal
chemistry in early drug discovery.
• Our findings suggest acoustic dispensing methods could improve HTS
results and avoid the development of misleading computational models
and statistical relationships.
• Automated pharmacophores are closer to pharmacophore generated
with acoustic data – all have hydrophobic features – missing from Tip-
based pharmacophore model
• Importance of hydrophobicity seen with logP correlation and
crystal structure interactions
• Public databases should annotate this meta-data alongside biological
data points, to create larger datasets for comparing different
computational methods.
17. Acoustic vs. Tip-based Transfers
-40 -20 0 20 40 60 80 100
Adapted from Spicer et al.,
Presentation at Drug Discovery
50
Acoustic % Inhibition
Serial dilution IC50 μM
Technology, Boston, MA, August
2005
10 20 30 40
Adapted from Wingfield.
Presentation at ELRIG2012,
Manchester, UK
NOTE DIFFERENT
0
0 10 20 30 40 50 ORIENTATION -40 -20 0 20 40 60 80 100
Acoustic IC50 μM Aqueous % Inhibition
104
Adapted from Wingfield et al.,
103
Amer. Drug Disco. 2007,
Log IC50 tips
Serial dilution IC50 μM
102 3(3):24
10
1
Data in this presentation
10-1
10-2
10-3
10-3 10-2 10-1 1 10 102 103 104
Acoustic IC50 μM Log IC50 acoustic
No Previous Analysis of molecule properties
18. Strengths and Weaknesses
• Small dataset size – focused on one compound series
• No previous publication describing how data quality can be
impacted by dispensing and how this in turn affects
computational models and downstream decision making.
• No comparison of pharmacophores generated from acoustic
dispensing and tip-based dispensing.
• No previous comparison of pharmacophores generated from in
vitro data with pharmacophores automatically generated from
X-ray crystal conformations of inhibitors.
• Severely limited by number of structures in public domain
with data in both systems
• Reluctance of many to accept that this could be an issue
• Ekins et al., PLOSONE, In press
19. The stuff of nightmares?
How much of the data in databases is generated by tip based serial
dilution methods
How much is erroneous
Do we have to start again?
How does it affect all subsequent science – data mining etc
Does it impact Pharmas productivity?
20. Simple Rules for licensing Could data ‘open accessibility’
“open” data equal ‘Disruption’
As we see a future of increased 1: NIH and other international
database integration the scientific funding bodies should
licensing of the data may be a mandate …open accessibility for
hurdle that hampers progress all data generated by publicly
and usability. funded research immediately
Williams, Wilbanks and Ekins.
Ekins, Waller, Bradley, Clark and
PLoS Comput Biol 8(9):
Williams. DDT, 18:265-71, 2013
e1002706, 2012
21. You can find me @... CDD Booth 205
PAPER ID: 13433
PAPER TITLE: “Dispensing processes profoundly impact biological assays and computational and statistical
analyses”
April 8th 8.35am Room 349
PAPER ID: 14750
PAPER TITLE: “Enhancing High Throughput Screening For Mycobacterium tuberculosis Drug Discovery
Using Bayesian Models”
April 9th 1.30pm Room 353
PAPER ID: 21524
PAPER TITLE: “Navigating between patents, papers, abstracts and databases using public sources and
tools”
April 9th 3.50pm Room 350
PAPER ID: 13358
PAPER TITLE: “TB Mobile: Appifying Data on Anti-tuberculosis Molecule Targets”
April 10th 8.30am Room 357
PAPER ID: 13382
PAPER TITLE: “Challenges and recommendations for obtaining chemical structures of industry-provided
repurposing candidates”
April 10th 10.20am Room 350
PAPER ID: 13438
PAPER TITLE: “Dual-event machine learning models to accelerate drug discovery”
April 10th 3.05 pm Room 350