- The document analyzes trends in bioactivity over time for three different targets: PIK3, ABL1, and DNA polymerase.
- For PIK3, the most active compound affinity has remained around 1-10pM, while the number of reported compounds has increased 1000-fold between 1994-2014.
- For ABL1, the proportion of highly active compounds reported has increased over time, and the total numbers of compounds reported peaked in 2006-2008.
- For DNA polymerase, the trend shows fewer compounds reported in recent years.
Presentation delivered by Colin Batchelor from the RSC eScience team at ACS New Orleans Spring Meeting April 2013.
There are dozens of public compound databases now available online, some of these providing access to tens of millions of chemical compounds. However, very little effort has been put into the delivery of databases of chemical reactions with the majority of large resources being commercial in nature. In our five years of delivering chemical based data resources to the chemistry community one of the primary requests has been that chemists want to know how to synthesize many of the chemicals they are researching. This presentation will provide an overview of our concerted efforts to enhance access to freely available chemistry data and will discuss the ChemSpider Reactions as an integrating hub of content including data extracted from US patents, from RSC Journals and databases and from our micro-publishing platform ChemSpider Synthetic Pages (CSSP).
Fire emissions from LUC: Promoting credibility and incentivesCIFOR-ICRAF
In this presentation Daniel Murdiyarso explains what the drivers of fire emissions from LUC are, how credibility can be promoted through MRV and what conclusions can be drawn.
Alternative animal model for compound characterizationWenlan Hu
To pick a model is not easy thing to do, especially when nutraceutical market needs have to be met. Such market requires low budget, fast turn-around rate, and high-quality data at the same time. Traditional models such as mice and cell cultures usually only meet one need at one time. IVB uses C.elegans and zebrafish which lies in the middle of the model spectrum in terms of the three needs to perfectly accommodate all of them at the same time.
Presentation delivered by Colin Batchelor from the RSC eScience team at ACS New Orleans Spring Meeting April 2013.
There are dozens of public compound databases now available online, some of these providing access to tens of millions of chemical compounds. However, very little effort has been put into the delivery of databases of chemical reactions with the majority of large resources being commercial in nature. In our five years of delivering chemical based data resources to the chemistry community one of the primary requests has been that chemists want to know how to synthesize many of the chemicals they are researching. This presentation will provide an overview of our concerted efforts to enhance access to freely available chemistry data and will discuss the ChemSpider Reactions as an integrating hub of content including data extracted from US patents, from RSC Journals and databases and from our micro-publishing platform ChemSpider Synthetic Pages (CSSP).
Fire emissions from LUC: Promoting credibility and incentivesCIFOR-ICRAF
In this presentation Daniel Murdiyarso explains what the drivers of fire emissions from LUC are, how credibility can be promoted through MRV and what conclusions can be drawn.
Alternative animal model for compound characterizationWenlan Hu
To pick a model is not easy thing to do, especially when nutraceutical market needs have to be met. Such market requires low budget, fast turn-around rate, and high-quality data at the same time. Traditional models such as mice and cell cultures usually only meet one need at one time. IVB uses C.elegans and zebrafish which lies in the middle of the model spectrum in terms of the three needs to perfectly accommodate all of them at the same time.
How to model longevity and health effect in 3 monthsWenlan Hu
Healthspan analysis is a huge part of longevity study, which is heavily looked at by many aging labs in recent years. The older we grow, our health will be affected accordingly, and this influence what type of compound we use. To better picture what effects compounds brings to us and to extend lifespan as a goal. A three stage compound assessment is developed by IVB to solve this question.
The compound characterization market is growing increasingly profitable and competitive at the same time. In order to develop a new compound product, the testing step is indispensable. Unlike drug discovery, compound testing is not as restrictive, but understanding the main workflow is still necessary to excel in the market. In order to help you improve both the efficiency and safety of compound testing, we developed the protocol to assist you in your findings.
Eric Boles - Healthy Animals = Healthy PlanetJohn Blue
Healthy Animals = Healthy Planet - Eric Boles, University of Arkansas, from the 2012 Annual Conference of the National Institute for Animal Agriculture, March 26 - 29, Denver, CO, USA.
More presentations at: http://www.trufflemedia.com/agmedia/conference/2012-decreasing-resources-increasing-regulation-advance-animal-agriculture
CRO Company for Mode of Action & Efficacy Test for Drugs | InvivoBiosystemsWenlan Hu
Compound testing takes shares of a huge part of the drug development and health-related compound market. In order to find a CRO that is both friendly for budget saving and efficient at the same time is not easy. IVB uses a three staged compound assessment which includes RNAseq, whole transcriptome analysis, and other techniques to help our clients better understand the mode of action and efficacy of a particular compound.
Finding Optimal Compound Dosage for Anti-Aging DrugsWenlan Hu
Anti-aging compound becomes a very integral part of the compound market. However, the lack of experience in this field makes it very hard for testing CROs to fully understand the mechanism of actions as well as efficacy of the compound, particularly the optimal dosage for anti-aging use. In the following slide we are trying to share with you the best way to do testing on the substances that are designed for anti-aging use.
Low cost nutraceutical hypothesis testingWenlan Hu
The US nutraceutical market is fast growing with increasingly demands on fast and economic nutraceutical testing labs. In order to succeed in a fast growing market, we need to review the market trends as well as the advantages of different model organisms in hypothesis testing.
Presentation for Texas A&M Superfund Research Center virtual learning series, Big Data in Environmental Science and Toxicology. More details at https://superfund.tamu.edu/big-data-session-2-aug-18-2021/
Different compounds behave in distinguished manner when tested. A important aspect of compound development is to understand the mode of action of compounds. In order to achieve this goal, IVB use RNAseq and whole transcriptome analysis to assist the findings. Based on the findings, a well-round understanding of a compound can be generated, which assists the research findings in a efficient and timely way.
Good Model Organism for Anti Aging TestingWenlan Hu
Drug testing is taking more attention than ever before in a fast growing market for longevity compounds. In order to succeed in a competitive market and develop a pipeline method for quick drug development, we need to understand and choose the most suitable model organism for aging studies. The following content is intended to provide information on how to choose the best model for anti-aging drug testing.
Results of research analysis to assess the impact of CARE Media Holding’s KidCARE TV program; evaluated on Product X on prescribing behavior of participating physicians using a nine month test/post-test period.
Learn how large-scale normalized data empowers the critical early phases of drug discovery.
To address the core concerns about data quality, comprehensiveness and comparability, the Reaxys product team has developed a completely new repository for bioactivity information. Reaxys Medicinal Chemistry stands as a unique source for normalized data in vitro efficacy, in vivo animal models, compound metabolism, pharmacokinetics and toxicity. This presentation takes a look at how this approach to data supports critical early discovery methods such as in silico screening and target profiling.
How to model longevity and health effect in 3 monthsWenlan Hu
Healthspan analysis is a huge part of longevity study, which is heavily looked at by many aging labs in recent years. The older we grow, our health will be affected accordingly, and this influence what type of compound we use. To better picture what effects compounds brings to us and to extend lifespan as a goal. A three stage compound assessment is developed by IVB to solve this question.
The compound characterization market is growing increasingly profitable and competitive at the same time. In order to develop a new compound product, the testing step is indispensable. Unlike drug discovery, compound testing is not as restrictive, but understanding the main workflow is still necessary to excel in the market. In order to help you improve both the efficiency and safety of compound testing, we developed the protocol to assist you in your findings.
Eric Boles - Healthy Animals = Healthy PlanetJohn Blue
Healthy Animals = Healthy Planet - Eric Boles, University of Arkansas, from the 2012 Annual Conference of the National Institute for Animal Agriculture, March 26 - 29, Denver, CO, USA.
More presentations at: http://www.trufflemedia.com/agmedia/conference/2012-decreasing-resources-increasing-regulation-advance-animal-agriculture
CRO Company for Mode of Action & Efficacy Test for Drugs | InvivoBiosystemsWenlan Hu
Compound testing takes shares of a huge part of the drug development and health-related compound market. In order to find a CRO that is both friendly for budget saving and efficient at the same time is not easy. IVB uses a three staged compound assessment which includes RNAseq, whole transcriptome analysis, and other techniques to help our clients better understand the mode of action and efficacy of a particular compound.
Finding Optimal Compound Dosage for Anti-Aging DrugsWenlan Hu
Anti-aging compound becomes a very integral part of the compound market. However, the lack of experience in this field makes it very hard for testing CROs to fully understand the mechanism of actions as well as efficacy of the compound, particularly the optimal dosage for anti-aging use. In the following slide we are trying to share with you the best way to do testing on the substances that are designed for anti-aging use.
Low cost nutraceutical hypothesis testingWenlan Hu
The US nutraceutical market is fast growing with increasingly demands on fast and economic nutraceutical testing labs. In order to succeed in a fast growing market, we need to review the market trends as well as the advantages of different model organisms in hypothesis testing.
Presentation for Texas A&M Superfund Research Center virtual learning series, Big Data in Environmental Science and Toxicology. More details at https://superfund.tamu.edu/big-data-session-2-aug-18-2021/
Different compounds behave in distinguished manner when tested. A important aspect of compound development is to understand the mode of action of compounds. In order to achieve this goal, IVB use RNAseq and whole transcriptome analysis to assist the findings. Based on the findings, a well-round understanding of a compound can be generated, which assists the research findings in a efficient and timely way.
Good Model Organism for Anti Aging TestingWenlan Hu
Drug testing is taking more attention than ever before in a fast growing market for longevity compounds. In order to succeed in a competitive market and develop a pipeline method for quick drug development, we need to understand and choose the most suitable model organism for aging studies. The following content is intended to provide information on how to choose the best model for anti-aging drug testing.
Results of research analysis to assess the impact of CARE Media Holding’s KidCARE TV program; evaluated on Product X on prescribing behavior of participating physicians using a nine month test/post-test period.
Learn how large-scale normalized data empowers the critical early phases of drug discovery.
To address the core concerns about data quality, comprehensiveness and comparability, the Reaxys product team has developed a completely new repository for bioactivity information. Reaxys Medicinal Chemistry stands as a unique source for normalized data in vitro efficacy, in vivo animal models, compound metabolism, pharmacokinetics and toxicity. This presentation takes a look at how this approach to data supports critical early discovery methods such as in silico screening and target profiling.
1. Time-based bioactivity analysis |
Presented By
Date
Time-Based Bioactivity Analysis
Reaxys Medicinal Chemistry
Matthew CLARK
18 May 2016
2. Time-based bioactivity analysis |
R&D Solutions
FOR PHARMA & LIFE SCIENCES
Essential Tools and Solutions for Pharma &
Life Sciences
https://www.elsevier.com/rd-solutions/pharma-and-life-
sciences-solutions
Matthew Clark, Ph. D. m.clark@elsevier.com
3. Time-based bioactivity analysis |
Q: can you analyze activity reported for a target over time, to see the time trend
of improvement?
A: Yes
Findings for PIK3 example
• While the most active compound has hovered around the 1-10pM range of
affinity, the scaffolds are similar
• Looking over the distribution of activities reported for all PIK3-active
compounds, the peak of the distribution has shifted only moderately over
time.
Findings for ABL1 example
• Most active compound about 10nM for some time
• Number of highly active compound reports increasing over time
• Trend is moving to more active compounds
Follow Up From Bioactivity Prediction Webinar Question
4. Time-based bioactivity analysis |
Most Potent Compound Reported for PIK3 Target by Year
(all variants, PIK3* )
The developer of the most-binding compound over time:
2014-16 – Pfizer
2011-13 – GSK (GSK2126458)
2008-10 – Pfizer
2000-07 – Isradipine, Sandoz
1994-96 – Nicarpidine, Syntex
9
10
11
12
13
1994-1996 1997-1999 2000-2002 2003-2005 2006-2007 2008-2010 2011-2013 2014-2016
The scaffolds have some
notable similarity over
this time period
5. Time-based bioactivity analysis |
• The peak of reported activities has shifted only moderately
• The number of compounds reported per year increased 1000 fold between
1994 and 2014
5
Distribution of Activities for PIK3 Target Over Time
Graph shows
the number of
assay reports
in each decade
of activity for
the given time
spans
That is, how
the activities
are distributed
Note: some
compounds are
reported in
more than one
time frame. 0
1000
2000
3000
4000
5000
6000
7000
8000
0 2 4 6 8 10 12
NumberofCompoundsReported
-log10[M] activity
1994-1996
1997-1999
2000-2002
2003-2005
2006-2008
2009-2011
2012-2014
2015-2016
6. Time-based bioactivity analysis |
• 1994-1996 compound is from Plexxicon, most active from Princeton U., most
recent from Nektar.
• 2000-2002 leader was Staurosporine!
6
ABL1 Kinase
6
7
8
9
10
11
12
1994-1996 1997-1999 2000-2002 2003-2005 2006-2007 2008-2010 2011-2013 2014-2016
7. Time-based bioactivity analysis |
• Proportion of highly active compound reports increasing over time
• Total number of compounds reported peaked in 2006-2008
7
ABL1 Kinase Distribution of Activities Over Time
0
500
1000
1500
2000
2500
0 2 4 6 8 10 12
NumberofCompoundsReported
-log10[M] activity
1994-1996
1997-1999
2000-2002
2003-2005
2006-2008
2009-2011
2012-2014
2015-2016
8. Time-based bioactivity analysis |
• Trend shows most active compounds have been small molecules, oligos, and
most recently the cyclic peptide cyclohexylgriselimycin
8
DNA Polymerase
6
7
8
9
10
11
12
1994-1996 1997-1999 2000-2002 2003-2005 2006-2007 2008-2010 2011-2013 2014-2016
9. Time-based bioactivity analysis | 9
DNA Polymerase Distribution of Activities over Time
0
100
200
300
400
500
600
0 2 4 6 8 10 12
NumberofCompoundsReported
-log10[M] activity
1994-1996
1997-1999
2000-2002
2003-2005
2006-2008
2009-2011
2012-2014
2015-2016
Trend seems to be for fewer compounds in recent years.
