in silico:
In a white
paper I wrote for the European Commission in 1988 I advocated the funding of
genome programs, and in particular the use of computers. In this endeavour I
coined "in silico" following "in vitro" and "in
vivo" I think that the first public use of the word is in the following
paper: A. Danchin, C. Médigue, O. Gascuel, H. Soldano, A. Hénaut, From
data banks to data bases. Res. Microbiol. (1991) 142: 913- 916. You
can find a developed account of this story in my book The
Delphic Boat, Harvard University Press, 2003 personal communication Antoine
Danchin, Institute Pasteur, 2003
Literally "in the computer".
Narrower
terms: in silico biology, in silico modeling, in silico
proteomics, in silico screening, in silico target discovery; Cell biology virtual cells
in silico;
Related terms: Chemoinformatics
rules of five
in silico
biology:
journal for
the advancement of computational models and simulations applied to complex
biological phenomena. We publish peer-reviewed leading-edge biological,
biomedical and biotechnological research in which computer-based (i.e., "in
silico") modeling and analysis tools are
developed and utilized to predict and elucidate dynamics of biological systems,
their design and control, and their evolution.
Scope Note In Silico Biology, IOS Press
https://www.iospress.nl/journal/in-silico-biology/
Related
terms: in silico, virtual cells
in
silico modeling:
Modeling of biological pathways and other biological
processes for drug discovery and development. Given the enormous increase in
genetic and molecular data, such models will continue to improve and are
predicted to become an essential tool for evaluating hypotheses, with only the
more promising ones being subjected to empirical testing.
in silico
screening: See also virtual
screening
in silico transcriptomics:
Omes & -omics
Integrated Pharma Informatics & Data Science March
11-13 2019 •
San Francisco, CA
Program |
Every facet of healthcare and medicine now generates and has access to enormous
amounts of data from across sources, organizations, and the world; the
pharmaceutical industry plays a key role in driving informatics for
translational research and precision medicine. The 11th Annual Integrated Pharma
Informatics program will discuss the challenges related to integrating,
analyzing, and interpreting data from clinical trials, sequencing, electronic
health records, and wearables. We will discuss informatics strategy for entire
organizations, from business goals to infrastructure and storage projects.
Special attention will be paid to artificial intelligence, machine learning,
natural language processing, and how companies are integrating these tools into
their informatics infrastructure. We will take a close look at how informatics
is driving translational and clinical research projects with a focus on data
standardization and integration.

LIMS Laboratory Information Management
Systems:
A basic LIMS is a passive bookkeeping system designed to keep
track of laboratory processes. It records the procedures that have been applied
to each sample, when a procedure was run, the machine or instrument that was
used, and who (e.g., which technician) did the work or was responsible for it.
It also records any run-specific parameters of the procedure, and the results if
any. In addition, a LIMS typically handles necessary administrative functions,
such as inventory management, monitoring of quality measures, resource planning
for instruments and personnel, and reporting. Related terms: robotic systems, robotics, sample prep,
Assays & Screening
medicinal
systems biology: This review will focus on the
development of a novel "chemical genetic/ genomic approach" that uses
small molecules to "probe and identify" the function of genes in
specific biological processes or pathways in human cells. Due to the close
relationship of small molecules with drugs, these systematic and integrative
studies will lead to the "medicinal systems biology approach" which is
critical to "formulate and modulate" complex biological (disease)
networks by small molecules (drugs) in human bio-systems. TK Kim, Chemical
genomics and medicinal systems biology: chemical control of genomic networks in
human systems biology for innovative medicine, J Biochem Mol Biol. 37(1):
53- 58, Jan 31, 2004 Related term: Bioinformatics systems
biology
molecular informatics:
interdisciplinary research on all molecular aspects
of bio/cheminformatics and computer-assisted molecular design. Molecular
Informatics presents methodological innovations that will lead to a deeper
understanding of ligand-receptor interactions, macromolecular complexes,
molecular networks, design concepts and processes that demonstrate how ideas and
design concepts lead to molecules with a desired structure or function,
preferably including experimental validation. Molecular Informatics
Journal, Scope Note, Wiley
http://www.wiley-vch.de/en/shop/journals/282-molecular-informatics-2022-en
molecular mimicry:
The process in
which structural properties of an introduced molecule imitate or simulate
molecules of the host. Direct mimicry of a molecule enables a viral protein
to bind directly to a normal substrate as a substitute for the homologous
normal ligand. Immunologic molecular mimicry generally refers to what can
be described as antigenic mimicry and is defined by the properties of antibodies
raised against various facets of epitopes on the viral protein. MeSH from
Immunology Letters 28 (2): 91- 99 May 1991
myGrid:
now the e-Science Lab
NeuroCommons:
The NeuroCommons project seeks to make all scientific research materials -
research articles, knowledge bases, research data, physical materials - as
available and as usable as they can be. We do this by fostering practices that
render information in a form that promotes uniform access by computational
agents - sometimes called "interoperability".
http://neurocommons.org/page/Main_Page
pharmaceutical bioinformatics:
a
new discipline in the area of the genomics revolution. It is central to
biomedicine with application in areas like pharmacy, medicine, biology and
medicinal chemistry. The genomics revolution has given high throughput methods
for massive gene sequencing, chemical synthesis and biological testing. This
creates oceans of new information. Pharmaceutical bioinformatics is all about
how to use all the new information effectively.
University of Uppsala, Pharmaceutical Bioinformatics http://www.pharmbio.org/

Pharmaceutical R&D
Informatics
Strategic Initiatives in Collaboration, Data Science, and Technologies
2019 April 17-18 Boston MA
There is no end in sight for the amount of data we can generate in
pharmaceutical R&D – the amount of clinical, translational, genomic, and
electronic health data we generate and collect necessitates effective
strategies and infrastructure for managing, integrating, and analyzing
these data for better decision making. As new tools and technologies –
from digital biomarkers to artificial intelligence – we must ensure that
our data is not only of high quality, but also correct and consistent.
Explores real-world projects and strategies for integrating and analyzing
complex data sets that are driving R&D and precision medicine.
http://www.bio-itworldexpo.com/drug-discovery-informatics
pharmacometrics:
an emerging science defined as the
science that quantifies drug, disease and trial information to aid
efficient drug development and/or regulatory decisions. Drug models
describe the relationship between exposure (or pharmacokinetics), response
(or pharmacodynamics) for both desired and undesired effects, and
individual patient characteristics. Disease models describe the
relationship between biomarkers and clinical outcomes, time course of
disease and placebo effects. The trial models describe the
inclusion/exclusion criteria, patient dis-continuation and adherence.
Typical focus of Pharmacometrics has been on drug models, also referred to
by terms such as: concentration-effect, dose-response, PKPD relationships.
These Pharmacometric analyses are designed, conducted and presented in the
context of drug development, therapeutic and regulatory decisions.
The single-most important strength of such analyses is its ability to
integrate knowledge across the development program and compounds, and
biology. US FDA, CDER, Pharmacometrics at FDA, CDER
https://www.fda.gov/aboutfda/centersoffices/officeofmedicalproductsandtobacco/cder/ucm167032.htm
FDA, CDER
Selected Pharmacometrics Reviews, Guidances and Presentations,
2018
https://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CDER/ucm225044.htm
can be defined as that branch of science
concerned with mathematical models of biology, pharmacology, disease, and
physiology used to describe and quantify interactions between xenobiotics
and patients (human and non-human), including beneficial effects and
adverse effects.[1] It
is normally applied to quantify drug, disease and trial information to aid
efficient drug development, regulatory decisions and rational drug
treatment in patients. Pharmacometrics uses models based on pharmacology, physiology and disease for
quantitative analysis of interactions between drugs and patients. This
involves
Systems pharmacology,
pharmacokinetics, pharmacodynamics and disease
progression with a focus on populations and variability.
Wikipedia accessed 2018 Sept 1
https://en.wikipedia.org/wiki/Pharmacometrics
Related terms: pharmacodynamics, pharmacokinetics
pre-competitive R&D
information:
Precompetitive R&D precludes:
(a) exchanging information among competitors relating to costs, sales,
profitability, prices, marketing, or distribution of any product, process,
or service that is not reasonably required to conduct the research and
development that is the purpose of such venture; (b) entering into any
agreement or engaging in any other conduct restricting, requiring, or otherwise
involving the production or marketing by any person who is a party to such
venture of any product, process, or service, other than the production
or marketing of proprietary information developed through such venture;
and (c) entering into any agreement or engaging in any other conduct that
is not reasonably required to prevent misappropriation of proprietary information
contributed by any person who is a party to such venture or its results. David. Hahn, Thomas Sporleder, ADE 601 Glossary Technical Terms for Agribusiness
Managers, Ohio State Univ. US* no longer on the web
May
be defined as the earliest point in the drug development process at which the
weight of evidence suggests that it is "reasonably likely" that the
key attributes for success are present and the key causes of failure are absent.
POC is multidimensional but is focused on attributes that, if not addressed,
represent a threat to the success of the project in crucial areas such as
safety, efficacy, pharmaceutics, and commercial and regulatory issues. The
appropriate weight of evidence is assessed through the use of mathematical
models and by evaluating the consequences of advancing a candidate drug that is
not safe, effective, or commercially viable, vs. failing to advance a candidate
that possesses these attributes. Tools for POC include biomarkers, targeted
populations, pharmacokinetic (PK)/pharmacodynamic (PD) modeling, simulation, and
adaptive study designs. Proof of Concept: A PhRMA Position Paper With
Recommendations for Best Practice, . Cartwright ME, et. al, Clin Pharmacol Ther.
2010 Feb 3.
http://www.ncbi.nlm.nih.gov/pubmed/20130568
Compare
with definitions in Business of
biopharmaceuticals
rational drug design:
In
contrast to traditional methods of drug
discovery (known as forward
pharmacology), which rely on trial-and-error testing
of chemical substances on cultured
cells or animals,
and matching the apparent effects to treatments, rational drug design (also
called reverse
pharmacology) begins with a hypothesis that
modulation of a specific biological target may have therapeutic value. In order
for a biomolecule to be selected as a drug target, two essential pieces of
information are required. The first is evidence that modulation of the target
will be disease modifying. This knowledge may come from, for example, disease
linkage studies that show an association between mutations in the biological
target and certain disease states.[15] The
second is that the target is "druggable".
This means that it is capable of binding to a small molecule and that its
activity can be modulated by the small molecule.[16]
Once a suitable target has been identified, the target is normally
cloned and
produced and purified.
The purified protein is then used to establish a screening
assay. In addition, the three-dimensional
structure of the target may be determined. The search for small molecules
that bind to the target is begun by screening libraries of potential drug
compounds. This may be done by using the screening assay (a "wet screen"). In
addition, if the structure of the target is available, a virtual
screen may be performed of candidate drugs.
Ideally the candidate drug compounds should be "drug-like",
that is they should possess properties that are predicted to lead to oral
bioavailability, adequate chemical and
metabolic stability, and minimal toxic effects.[17] Several
methods are available to estimate druglikeness such as Lipinski's
Rule of Five and a range of scoring methods
such as lipophilic
efficiency.[18] Several
methods for predicting drug metabolism have also been proposed in the scientific
literature.[19]
Due to the large number of drug properties that must be simultaneously
optimized during the design process, multi-objective
optimization techniques are sometimes
employed.[20] Finally
because of the limitations in the current methods for prediction of activity,
drug design is still very much reliant on serendipity[21] and bounded
rationality.[22]
Wikipedia accessed 2018 Sept 10
https://en.wikipedia.org/wiki/Drug_design#Rational_drug_discovery
Related
terms :
structure based drug design
Combinatorial
Libraries & synthesis: rational library design, computational quantum
chemistry
receptor mapping:
The technique used to describe the geometric and/or
electronic features of a binding site when insufficient structural data for this
receptor or enzyme
are available. Generally the active site cavity is defined by comparing the
superposition of active to that of inactive molecules. IUPAC Medicinal
Chemistry, IUPAC Compendium
Over the past ten to fifteen years [before
1987], receptor mapping has expanded from a very minor technique, besieged
by problems and limited in its approach, to one that is widespread, extended
beyond receptors and applied to clinical problems and populations with
modern imaging and scanning techniques.
MJ Kuhar "Imaging receptors for
drugs in neural tissue" Neuropharmacology 1987 Jul. 26 (7B):
911-6
simulations:
Up until now, biomolecular simulations in drug design
have been of limited use because of the short time scales, long turnaround
times (implying poor sampling), the limited accuracy of simulations alluded
to above, and the relatively small size of systems simulated when one wishes
to account for proper inclusion of the physiological environment like membranes
and solvent. Developing a new drug goes beyond finding binding compounds
and must rely on good properties from the outset: activity, absorption,
distribution, metabolism, excretion. Pharmacological researchers would
like to predict these properties first, before one optimizes activity as
conventionally done, and before analogs are made. ... When sufficient resources
are available, simulations can determine the relative free energy values
of drugs passing through membranes. These values are required to estimate
the bioavailability of drugs. Opportunities in Molecular Biomedicine
in the Era of Teraflop Computing March 3 & 4, 1999, Rockville,
MD, NIH Resource for Macromolecular Modeling and Bioinformatics Beckman
Institute for Advanced Science and Technology, University of Illinois at Urbana-
Champaign
Molecular Biomedicine in the Era of Teraflop Computing - DDDAS.org
soft
drug design:
Soft drug design represents a new approach aimed to design
safer drugs with an increased therapeutic index by integrating metabolism
considerations into the drug design process. Soft drugs are new therapeutic
agents that undergo predictable metabolism to inactive metabolites after
exerting their therapeutic effect. Hence, they are obtained by building into the
molecule, in addition to the activity, the most desired way in which the
molecule is to be deactivated and detoxified.
Soft
drug design: general principles and recent applications. Bodor N, Buchwald
P.
Med
Res Rev. 2000 Jan;20(1): 58-101
Related term: Microarrays small
molecule microarrays
Software
Applications & Services 2019 April 16-18 Boston MA As data
generation increases, there is a need for workflows that are reproducible
across infrastructures, able to empower scientists and researchers to
apply cutting-edge analysis methods. A main challenge is scientific data
is not centralized or standardized and is fragmented – from
instrumentation to clinical research to legacy software. The Software
Applications & Services track explores how biopharma companies are
utilizing software tools to leverage data platforms to advance data
strategies. Themes of case studies that will be presented will focus on
data analytics approaches, data methods and standards approaches,
transparency, efficiency, security, and cost-effective solutions.
http://www.bio-itworldexpo.com/software
structure:
In a biological or
anatomical context, the term structure is associated with two distinct concepts
(meanings): 1. a material object generated as a result of coordinated gene
expression, which necessarily consists of parts (e.g., hemoglobin molecule,
cell, heart, human body); and 2. the manner of organization or interrelation of
the parts that constitute a structure specified by the first definition (i.e.,
the structure of a structure). Both definitions emphasize the critical need for
declaring the principles according to which units of organization can be defined
in order to be able to state what is 'whole' and what is 'part'. Specifying the
manner in which parts interrelate must satisfy two requirements: 1. to determine
the kinds of parts of which various structures may be constituted; and 2. to
state the manner of spatial organization of parts by describing their
boundaries, continuities and attachments, as well as their location, orientation
and spatial adjacencies in terms of qualitative coordinates (in addition to the
quantitative geometric coordinates, which are embedded in the Visible Human data
sets). Cornelius Rosse, et. al., Visible Human, Know Thyself: The Digital
Anatomist Dynamic Structural Abstraction, National Library of Medicine, US
https://www.nlm.nih.gov/archive/20120702/research/visible/vhpconf2000/AUTHORS/ROSSE/TEXTINDX.HTM
Related terms: Cell
biology, Expression Compare
unstructured.
structure
based design: A design strategy
for new chemical entities based on the three- dimensional (3D) structure
of the target obtained by X-ray or nuclear magnetic resonance (NMR)
studies, or from protein homology models. IUPAC Computational
structure-based drug design: the
design and optimization of a chemical structure with the goal of
identifying a compound suitable for clinical testing — a drug candidate.
It is based on knowledge of the drug’s three-dimensional structure and how
its shape and charge cause it to interact with its biological target,
ultimately eliciting a medical effect.
https://www.nature.com/subjects/structure-based-drug-design
Structure-based drug
design (or direct drug design) relies on knowledge of the three
dimensional structure of the
biological target obtained through methods such as x-ray
crystallography or NMR
spectroscopy.[34] If
an experimental structure of a target is not available, it may be possible
to create a homology
model of the target based on the
experimental structure of a related protein. Using the structure of the
biological target, candidate drugs that are predicted to bind with
high affinity and selectivity to
the target may be designed using interactive graphics and the intuition of
a medicinal
chemist. Alternatively various
automated computational procedures may be used to suggest new drug
candidates.[35]
Current methods for
structure-based drug design can be divided roughly into three main
categories.[36] The
first method is identification of new ligands for a given receptor by
searching large databases of 3D structures of small molecules to find
those fitting the binding pocket of the receptor using fast approximate docking programs.
This method is known as virtual
screening. A second category is de
novo design of new ligands. In this method, ligand molecules are built up
within the constraints of the binding pocket by assembling small pieces in
a stepwise manner. These pieces can be either individual atoms or
molecular fragments. The key advantage of such a method is that novel
structures, not contained in any database, can be suggested.[37][38][39] A
third method is the optimization of known ligands by evaluating proposed
analogs within the binding cavity.[36]
Wikipedia accessed 2018 Oct 26
https://en.wikipedia.org/wiki/Drug_design#Structure-based
systems biology:
Bioinformatics
top-down:
A systems approach, which looks at the big picture
and complexity. Genomics is essentially a top- down approach, the opposite
of a bottom- up approach. Our ways of thinking have been so profoundly
influenced by bottom- up, reductionist approaches that we are having to
learn to think in very different ways to begin to fully exploit genomic
data. Narrower term: Nanoscience &
miniaturization nanofabrication- top- down
translational research:
is one of the most important activities of translational medicine as it
supports predictions about probable drug activities across species and is
especially important when compounds with unprecedented drug targets are brought
to humans for the first time. Translational research has the potential to
deliver many practical benefits for patients and justify the extensive
investments placed by the private and public sector in biomedical research.
Translational research encompasses a complexity of scientific, financial,
ethical, regulatory, legislative and practical hurdles that need to be addressed
at several levels to make the process efficient. What's
next in translational medicine? Littman BH, Di Mario L, Plebani M, Marincola FM.
What's next in translational medicine? Clin Sci (London) 112 (4): 217- 227, Feb
2007 Related terms: Molecular Medicine clinical
proteomics translational
medicine biomarker validation
Virtual Cell:
VCell, (Virtual Cell) is a comprehensive platform for modeling cell biological
systems that is built on a central database and disseminated as a web
application.,
http://vcell.org/
Related terms: -Omes & -omics metabolome,
transcriptome
Drug
discovery informatics Resources
Catalyzing
Inquiry at the Interface of Computing and Biology,
Edited
by John C Wooley and Herbert S Lin. National Research Council (US) Committee on
Frontiers at the Interface of Computing and Biology. Washington (DC): National
Academies Press (US); 2005. ISBN-10: 0-309-09612-X
Folding@home http://folding.stanford.edu/
Glossary of data management terms, Cornell University
https://data.research.cornell.edu/content/glossary
IUPAC International Union of Pure and Applied Chemistry, Glossary of Terms Used
in Combinatorial Chemistry, D. Maclean, J. J. Baldwin, V.T. Ivanov, Y. Kato, A.
Shaw, P. Schneider, and E. M.. Gordon, Pure Appl. Chem., Vol. 71, No. 12, pp.
2349-2365, 1999. 100+ definitions. http://www.iupac.org/reports/1999/7112maclean
IUPAC International Union of Pure and Applied Chemistry, Compendium of
Chemical Terminology: Recommendations, compiled by Alan D. McNaught and
Andrew Wilkinson, Blackwell Science, 2012. "Gold Book" 6500+
definitions. http://goldbook.iupac.org/
IUPAC International Union of Pure and Applied Chemistry, Glossary of Terms
used in Computational Drug Design, Part II 2015
https://www.degruyter.com/downloadpdf/j/pac.2016.88.issue-3/pac-2012-1204/pac-2012-1204.pdf
How
to look for other unfamiliar terms
IUPAC definitions are reprinted with the permission of the International
Union of Pure and Applied Chemistry.