In the world of pharma precompetitive efforts are increasing. These developments have created a dynamic ecosystem with pharma as smaller nodes in a complex network, in which collaborations have become an important business model.
With the recent announcement that GlaxoSmithKline have released a huge tranche of whole cell malaria screening data to the public domain, accompanied by a corresponding publication, this raises some issues for consideration before this exemplar instance becomes a trend. We have examined the data from a high level, by studying the molecular properties, and consider the various alerts presently in use by major pharma companies. We acknowledge the potential value of such data but also raise the issue of the actual value of such datasets released into the public domain. We also suggest approaches that could enhance the value of such datasets to the community and theoretically offer more immediate benefit to the search for leads for other neglected diseases.
A unified platform providing functionality based on role is a logical progression in eClinical technology development, with the majority of sponsors/CROs preferring and supporting this evolution.
With the recent announcement that GlaxoSmithKline have released a huge tranche of whole cell malaria screening data to the public domain, accompanied by a corresponding publication, this raises some issues for consideration before this exemplar instance becomes a trend. We have examined the data from a high level, by studying the molecular properties, and consider the various alerts presently in use by major pharma companies. We acknowledge the potential value of such data but also raise the issue of the actual value of such datasets released into the public domain. We also suggest approaches that could enhance the value of such datasets to the community and theoretically offer more immediate benefit to the search for leads for other neglected diseases.
A unified platform providing functionality based on role is a logical progression in eClinical technology development, with the majority of sponsors/CROs preferring and supporting this evolution.
Presentation Alliance of European Life Sciences Law Firms
(Julian Hitchcock and Sofie van der Meulen) on legal aspects of big data in pharma. Topics: privacy, IP, medical devices and IVD.
The Role of the FAIR Guiding Principles for an effective Learning Health SystemMichel Dumontier
he learning health system (LHS) is an integrated social and technological system that embeds continuous improvement and innovation for the effective delivery of healthcare. A crucial part of the LHS lies in how the underlying information system will secure and take advantage of relevant knowledge assets towards supporting complex and unusual clinical decision making, facilitating public health surveillance, and aiding comparative effectiveness research. However, key knowledge assets remain difficult to obtain and reuse, particularly in a decentralized context. In this talk, I will discuss the role of the Findable, Accessible, Interoperable, and Reusable (FAIR) Guiding Principles towards the realization of the LHS, along with emerging technologies to publish and refine clinical research and knowledge derived therein.
Keynote given for 2021 Knowledge Representation for Health Care http://banzai-deim.urv.net/events/KR4HC-2021/
Doing more with less resources used to be a situation common just for academic scientists. This is unfortunately still true for academics but we are seeing others facing many of the same challenges. With the squeeze on budgets and cost cutting resulting from recent worldwide economic challenges, the failure of many drugs to make it through the pipeline to the market, and the increasing costs associated with the drug development process, we are now seeing in the pharmaceutical industry a dramatic shift, perhaps belatedly, to have to accommodate similar challenges of doing more with less
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)Hellmuth Broda
While we bemoan the ever increasing data tsunami new technologies allow to harvest the gold nuggets in the hay stack.
Using the example of the Pharmaceutical Industry some of the possible business uses for Big Data Analitics are outlined.
Open science and medical evidence generation - Kees van Bochove - The HyveKees van Bochove
Presentation about open science, the FAIR principles, and medical evidence generation with the OHDSI COVID-19 study-a-thon as an example. I've used variations on this deck in a couple of classroom and online courses for PhD and master students early 2020.
Sharing and standards christopher hart - clinical innovation and partnering...Christopher Hart
Acknowledging the increasing need for cooperation and collaboration in data sharing and access. Describing the complexity that this can bring. Then describing some of the ways to simplify that.
Originally presented at Terrapin's Clinical innovation and partnering world March 8-9 2017.
http://www.terrapinn.com/conference/innovation-and-partnering/index.stm
As many blockbuster drugs reach their patent cliffs, pharmaceutical companies and their service providers are searching to make drug development a more efficient process. Here are just a few of the trends to look for in the coming years.
Learn more: http://bit.ly/1LSIgwJ
ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY "AN OVERVIEW OF AWARENESS"FinianCN
ARTIFICIAL INTELLIGENT IN DRUG DISCOVERY:- AN OVERVIEW OF AWARENESS.
AI is showing the potential to be a faster and more efficient way to find and develop new drugs. A growing number of organizations and universities are focusing to minimize the complexities involved in the classical way of drug discovery by using AI computing to envisage which drug candidate are most likely to be effective treatments.
It is hard to measure the adoption of AI in drug discovery. Pharma and biotech companies tend to not publicly disclose competitive technology use.
While organizations are adopting the technology, there is significant untapped potential for those willing to be more aggressive. Which is depending on the realization of the potential with education and relevant success stories
This lecture outlines the different strategies for finding a fragment hit and the subsequent elaboration strategies used in order to increase potency to develop a lead compound in drug discovery.
Presentation Alliance of European Life Sciences Law Firms
(Julian Hitchcock and Sofie van der Meulen) on legal aspects of big data in pharma. Topics: privacy, IP, medical devices and IVD.
The Role of the FAIR Guiding Principles for an effective Learning Health SystemMichel Dumontier
he learning health system (LHS) is an integrated social and technological system that embeds continuous improvement and innovation for the effective delivery of healthcare. A crucial part of the LHS lies in how the underlying information system will secure and take advantage of relevant knowledge assets towards supporting complex and unusual clinical decision making, facilitating public health surveillance, and aiding comparative effectiveness research. However, key knowledge assets remain difficult to obtain and reuse, particularly in a decentralized context. In this talk, I will discuss the role of the Findable, Accessible, Interoperable, and Reusable (FAIR) Guiding Principles towards the realization of the LHS, along with emerging technologies to publish and refine clinical research and knowledge derived therein.
Keynote given for 2021 Knowledge Representation for Health Care http://banzai-deim.urv.net/events/KR4HC-2021/
Doing more with less resources used to be a situation common just for academic scientists. This is unfortunately still true for academics but we are seeing others facing many of the same challenges. With the squeeze on budgets and cost cutting resulting from recent worldwide economic challenges, the failure of many drugs to make it through the pipeline to the market, and the increasing costs associated with the drug development process, we are now seeing in the pharmaceutical industry a dramatic shift, perhaps belatedly, to have to accommodate similar challenges of doing more with less
Big Data and its Impact on Industry (Example of the Pharmaceutical Industry)Hellmuth Broda
While we bemoan the ever increasing data tsunami new technologies allow to harvest the gold nuggets in the hay stack.
Using the example of the Pharmaceutical Industry some of the possible business uses for Big Data Analitics are outlined.
Open science and medical evidence generation - Kees van Bochove - The HyveKees van Bochove
Presentation about open science, the FAIR principles, and medical evidence generation with the OHDSI COVID-19 study-a-thon as an example. I've used variations on this deck in a couple of classroom and online courses for PhD and master students early 2020.
Sharing and standards christopher hart - clinical innovation and partnering...Christopher Hart
Acknowledging the increasing need for cooperation and collaboration in data sharing and access. Describing the complexity that this can bring. Then describing some of the ways to simplify that.
Originally presented at Terrapin's Clinical innovation and partnering world March 8-9 2017.
http://www.terrapinn.com/conference/innovation-and-partnering/index.stm
As many blockbuster drugs reach their patent cliffs, pharmaceutical companies and their service providers are searching to make drug development a more efficient process. Here are just a few of the trends to look for in the coming years.
Learn more: http://bit.ly/1LSIgwJ
ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY "AN OVERVIEW OF AWARENESS"FinianCN
ARTIFICIAL INTELLIGENT IN DRUG DISCOVERY:- AN OVERVIEW OF AWARENESS.
AI is showing the potential to be a faster and more efficient way to find and develop new drugs. A growing number of organizations and universities are focusing to minimize the complexities involved in the classical way of drug discovery by using AI computing to envisage which drug candidate are most likely to be effective treatments.
It is hard to measure the adoption of AI in drug discovery. Pharma and biotech companies tend to not publicly disclose competitive technology use.
While organizations are adopting the technology, there is significant untapped potential for those willing to be more aggressive. Which is depending on the realization of the potential with education and relevant success stories
This lecture outlines the different strategies for finding a fragment hit and the subsequent elaboration strategies used in order to increase potency to develop a lead compound in drug discovery.
Gave a talk at StartCon about the future of Growth. I touch on viral marketing / referral marketing, fake news and social media, and marketplaces. Finally, the slides go through future technology platforms and how things might evolve there.
The Six Highest Performing B2B Blog Post FormatsBarry Feldman
If your B2B blogging goals include earning social media shares and backlinks to boost your search rankings, this infographic lists the size best approaches.
Each technological age has been marked by a shift in how the industrial platform enables companies to rethink their business processes and create wealth. In the talk I argue that we are limiting our view of what this next industrial/digital age can offer because of how we read, measure and through that perceive the world (how we cherry pick data). Companies are locked in metrics and quantitative measures, data that can fit into a spreadsheet. And by that they see the digital transformation merely as an efficiency tool to the fossil fuel age. But we need to stretch further…
32 Ways a Digital Marketing Consultant Can Help Grow Your BusinessBarry Feldman
How can a digital marketing consultant help your business? In this resource we'll count the ways. 24 additional marketing resources are bundled for free.
Study: The Future of VR, AR and Self-Driving CarsLinkedIn
We asked LinkedIn members worldwide about their levels of interest in the latest wave of technology: whether they’re using wearables, and whether they intend to buy self-driving cars and VR headsets as they become available. We asked them too about their attitudes to technology and to the growing role of Artificial Intelligence (AI) in the devices that they use. The answers were fascinating – and in many cases, surprising.
This SlideShare explores the full results of this study, including detailed market-by-market breakdowns of intention levels for each technology – and how attitudes change with age, location and seniority level. If you’re marketing a tech brand – or planning to use VR and wearables to reach a professional audience – then these are insights you won’t want to miss.
Whitepaper developed with Pharma Exec magazine on how EIM- Enterprise Information Management- can provide efficiency and kick start innovation by ensuring information flows correctly inside- and outside- the company
Collision Forces: Scientific Integrity Meets the Capital MarketsLindsay Meyer
The landscape for innovation in the life sciences requires substantial participation from the investment community to finance new ventures and support existing projects. As such, appropriate risk-adjusted returns are expected by investors. Gaining insight into the progress of important clinical trials has catalyzed an information asymmetry between direct participants in the scientific process and the investment community. Direct participants can gain materially by breaching confidentiality agreements or engaging in insider trading, unethical practices that compromise scientific integrity. This report explores the nature of conflicts that can arise from the unique relationships specific to entities developing human therapeutics and proposes three mechanisms for minimizing negative externalities of the research process: raising awareness of the problem, mandating professional organizations to adopt and enforce strict policies for sharing material information, and establishing project work teams to limit the number of individuals exposed to non-public information.
Lighting the Way - The Era of the ARO (European Pharmaceutical Contractor, Au...Cyrus Park
We are entering a new era of the ARO, one that challenges the current paradigm of clinical development and the numerous offerings of CROs. It will not be long before AROs play a more central role in pharmaceutical clinical development plans.
AROs, like Julius Clinical, have evolved over the years, giving rise to various definitions of what an ARO is and what it isn’t. In this opinion piece, published in the European Pharmaceutical Contractor (EPC) magazine, Cyrus Park highlights four common misperceptions about academic research organizations (AROs) and attempts to dispel some of the misconceptions from his own observations. The full article can be read here.
This presentation outlines a mechanism for using the power of "Big Data", social networking and technology infrastructure to speed the process of curing a horrible disease.
I have framed this talk to encourage Pharmacy students to embrace computing in general, and data science and artificial intelligence techniques in particular. The reason is that data-driven science has overtaken traditional lab science; chemistry and biology that underlie pharmacy have become data-driven sciences, and a significant majority of the new jobs in pharma industries demand data analysis skills. Increasingly, traditional bioinformatics approaches are being complemented or replaced by machine learning or deep learning algorithms, especially for cases that have large data sets. I will provide a few examples (e.g., drug discovery, finding adverse drug reactions and broadly pharmacovigilance, and selecting patients for clinical trials) to demonstrate how big data and/or AI are indispensable to pharma research and industry today.
The role of the FAIR Guiding Principles in a Learning Health SystemMichel Dumontier
The learning health system (LHS) is a concept for a socio-technological system that continuously improves the delivery of health care by coupling biomedical research with practice- and evidence- based medicine. Key aspects of the LHS are collecting, integrating, and analyzing data from different sources. While the increased digitalisation of healthcare is creating new data sources, these remain hard to find and use, let alone make use of as part of intelligent systems for the benefit of patients, healthcare providers, and researchers. This talk will examine recent developments towards making key parts of the LHS, such as clinical practice guidelines, Findable, Accessible, Interoperable, and Reusable (FAIR).
FasterCures Presentation: Fostering innovation while delivering treatments an...TRAIN Central Station
FasterCures' Margaret Anderson presents at the 2009 BioEconomy Summit Healthcare Policy Session 2: Affordability and Access. Presents new business models to accelerate research.
Presentation about OHSL's new initiative, Mycroft Cognitive Assistant®, which is intended to streamline the operational aspects of research using IBM Watson cognitive computing capabilities.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality
Disruptive Strategies for Removing Drug Discovery Bottlenecks
1. POLICY FORUM
DRUG DISCOVERY
Disruptive Strategies for Removing Drug Discovery Bottlenecks
Sean Ekins1 *, Chris L. Waller2, 3 Mary P. Bradley4 and Antony J. Williams5
1
Collaborations in Chemistry, 5616 Hilltop Needmore Road, Fuquay-Varina, NC 27526,
U.S.A.
2
Pfizer Inc., Eastern Point Road, Groton, CT 06340.
3
School of Pharmacy, University of North Carolina, Chapel Hill, NC 27514
4
CollaborationFinder, Harvard Square, One Mifflin Place, Suite 400, Cambridge, MA
02138
5
Royal Society of Chemistry, 904 Tamaras Circle, Wake Forest, NC 27587.
* To whom correspondence should be addressed.
Sean Ekins, E-mail address: ekinssean@yahoo.com, Phone: +1 215 687 1320
1
2. HTS, bottlenecks and databases
Currently large pharmaceutical companies are undergoing selective disintegration,
while contract research organizations (CROs) and academia are growing in influence,
publicly-funded drug development programs are expanding, precompetitive efforts are
increasing, along with a re-emergence of venture-backed biotechnology firms (1). These
developments have created a dynamic ecosystem with pharma as smaller nodes in a
complex network, in which collaborations have become an important business model.
However, we are seeing a shift in focus away from early drug discovery, counter to what
some have suggested is necessary for the industry to survive post disintegration (2).
This is exemplified by the shift of high throughput screening (HTS) for drug
discovery from a small number of major pharmaceutical companies to a larger number of
academic and institutional laboratories in the US. This seems counter intuitive as some
drugs and a large percentage of leads are discovered using HTS (3), yet there are also
examples in which HTS fails, in particular antibacterial research and other areas (4, 5).
Learning from the pharma experience with HTS is instructive. A recent study identified
78 academic screening centers in the US focused on high risk drug targets, while there
were major gaps for efficacy testing, drug metabolism, PK studies and the challenge of
translation to the clinic (6), commonly termed the “valley of death”. These gaps
incidentally are all skills that pharma is removing and outsourcing. This leaves only
CROs and clinically affiliated institutes able to overcome this bottleneck. Another issue
identified by researchers from Bayer indicates that literature data on potential drug targets
is not reproducible (7). Translating more compounds to the clinic from HTS screening
2
3. centers, may indicate that many would likely fail without controlling for bias in pre-
clinical proof of concept studies and target-based discovery to improve clinical success
(8). Taking HTS out of pharmaceutical companies has not achieved innovative
breakthroughs. And yet, the US government through different agencies is investing
heavily in large HTS initiatives such as ToxCast (9, 10), Tox21 (11), Molecular Libraries
Probe Production Centers Network (MLPCN) (12), National Center for Translational
Therapeutics (NCATS) (13), the LINCS project (14) alongside the institutional screening
centers, with little apparent coordination or consideration of the outputs. We have
concerns regarding simply using the HTS assays (and data) that were optimized to
minimize “false negatives” for risk assessment purposes.
A crowdsourcing evaluation of MLPCN probes suggested to us that academic
screening may result in a large number of dubious leads when in a drug screening mode
(12). All of the screening efforts are generating very large quantities of data and there
would be an expectation that it is freely accessible, requiring databases that can handle
structures and multiple bioactivity endpoints. Recent NIH funded efforts with the NPC
browser (15) suggest this is not straightforward (16) and poor data quality will severely
impact the cost effective but increasingly informatics dependent tools being used for
repurposing efforts (17). In our opinion there needs to be independent assessment and
curation of the data produced across the board before embarking on more investments.
It is also unclear how such data is policed to make sure it goes out in a timely
manner for maximal exposure. We are not aware of any funding agency mandating data
to be published along with quality guidelines, although we have suggested granting
3
4. bodies should have minimal quality standards for published data (16). An extension to
this would be that all data generated from publicly funded research should be openly
available, within a year of generation, in high quality internet databases.
We think part of the current trend in terms of proliferation of HTS screening
initiatives is due to lack of coordination of government agencies, creating duplication and
overlap, as exemplified by numerous chemical databases in North America containing
approved drugs (Table 1). The government agencies would argue that redundancy in
funding mitigates risk, however if there is no sharing of data or experience ex post facto,
then the risk of duplicative failure and unproductive expenditure increases. From what we
see there is too little collaboration around databases, curation, data quality (16) or even
openness across the board.
There has been much discussion in the context of NCATS, about the urgent need
to revamp how drugs are developed, brought to market faster and what incentives can be
provided to generate treatments for neglected and rare diseases (13). We question
however whether any government or academic institute as they currently stand can
adequately pursue such goals when an entire industry is struggling with the same
challenges. Many of the techniques proposed (13), just like HTS, will not dramatically
impact the process alone because this has not occurred in pharma.
Public private partnerships and translational informatics
This begs the question of how we can remove the bottlenecks impeding progress
now. Academic groups could avoid the “valley of death”, by working more closely with
CROs and virtual pharmas to do more preclinical and development studies, who in turn
4
5. will work with pharmas to purchase the most promising compounds. To do this there
needs to be an awareness of what research is going on in the screening centers, and they
in turn should be aware of groups that can take their hits.
There is general agreement that the key to breakthrough success is collaboration
(18). There is also consensus that social networking can provide an effective platform for
increasing collaboration in biomedical research (19), yet to date this has failed to take
hold. The reason is fundamental: monetization of intellectual property (IP). There is no
incentive for research organizations to disclose their current research in an open social
networking forum where competitors have equal access. This is even true in academic
research where investigators compete for funding. The key to success of this model of
collaboration is the security of IP and the ability to selectively disclose IP to a valid
potential partner in a secure way that results in a mutually equitable outcome for all
parties (20). Research collaborations are currently most advanced in the areas of
neglected diseases, where funding comes primarily from public sources, data is more
open, and potential profits are low or nil. The same situation is true for rare diseases (21,
22) and one would expect the creation of networks and ways to do more with less funding
using collaborative software (18, 23) will be essential. In both neglected and rare diseases
the partners are more likely to share IP because the monetary value of the IP ceases to be
a barrier.
Given that research organizations appear to be open to embracing a new paradigm
of collaboration, how is one scientist to know what other work is currently ongoing in a
specific therapeutic or disease area when this is private? The key areas for success in
biomedical research collaborations are for organizations to be able to “identify best-in-
5
6. class capability, evaluate opportunities presented by programs and understand the
associated risks” (24). To date, there is a lack of support mechanisms to identify and
foster collaborations, resulting in a time consuming hit-or-miss process that relies on
networking, internet searching, and attending scientific conferences. New services (25)
that provide a low cost, efficient means of finding targeted scientific connections for
research and funding, while protecting intellectual property will be key to connect
everyone with a role in drug discovery and development. As virtual companies will have
nowhere near the resources or experience of a big pharma, much more work will need to
be performed in silico (17) as well as in a collaborative manner (18) to ensure likely
success. Another way to look at this is that a new virtual team paradigm has the potential
to innovate through disruption.
There have been several collaborative public private partnerships (PPP) in Europe
to share drug safety data (26), ontologies and models (27) and knowledge management of
pharmacological data (28), all of which foster collaboration, as well as data sharing from
industry and academia. In comparison the USA has nothing comparable currently
ongoing in its research portfolio. Such shared knowledge could help virtual pharmas,
academics and institutes alongside pre-competitive initiatives like those in informatics
(29-32) to focus on the best ideas. The key challenge here is to ensure the delivery of
tools or services to solve common problems to all parties involved and that there is
coordination, progress and no overlap with the PPP initiatives described above. All of
these efforts lower the cost of research and remove duplication of efforts. A direct
example is the structure representation standards documented for the FDA’s substance
registration system (33) whose recommendations have largely been adopted by ChEMBL
6
7. (34) and will be implemented into ChemSpider (35) to support the OpenPHACTS
project (28) for pharmaceutical companies that are participating in this initiative.
As big pharma relies more on the CROs and academics, they will focus on
translational informatics (integrated software solutions to manage the logistics, data
integration and collaboration) and other efforts such as Pfizer’s ePlacebo. This uses
placebo dosing data from previously executed clinical trials to augment or potentially
supplant the need for placebo control groups in clinical trials. A cross-pharma data
sharing consortium would dramatically impact the cost associated with clinical trial
recruitment and execution of placebo dosing. In an effort to stimulate data sharing of this
type the FDA has announced an overhaul of its IT infrastructure (36). A first step is the
effort to make the historical clinical data in the FDA’s vaults public to be followed by a
vast amount of de-identified post market surveillance data. By doing this, the FDA hopes
that the open access movement will stimulate the creation of public private partnerships
aimed at sharing data relevant to other drug development stages. Could they go further
and mandate all de-identified clinical data be made public as part of the cost of doing
business? Although some groups are pro (37) and others con (38) this approach could be
universally useful for health research. We should be aware of potential barriers to data
sharing and collaboration. Data and information silos exist at all levels of organizations.
Allowing for data/information integration across silos is not a technological problem,
regardless of issues of taxonomies and ontologies, but those will be much easier to
surmount than the cultural, societal, and behavioral barriers to effective collaboration
(18). Such non-technical issues generally inhibit translational data analysis on a broad
7
8. scale. With all the distributed research efforts we do not want to see creation of new data
silos.
Mining by swarm and finding the best collaborators
While the FDA and the NHS (39) have discussed the ‘big data’ or ‘analytics’
future involving analysis of patient data. We are also moving into the era of drug safety
analysis, drug repurposing and marketing by sentiment analysis using social media
stream mining tools (40-42). Swarm intelligence is a new subfield of bio-inspired
artificial intelligence offering solutions to complex problems like pooled health-related
data from different organizations as well as real time data from social networks (43).
Emerging and likely disruptive technologies that listen to the crowd passively do not
appear to be on the agenda (36).
In summary, if we are to remove bottlenecks we need to provide more confidence
that lead compounds will have efficacy in vivo and be safe. Some of these aspects could
be considered using predictive models already assembled and exclusive to the
pharmaceutical companies. Sharing precompetitive data and models (44, 45), whether
through a PPP or collaborations, could provide more confidence in the quality of the
leads produced such that they will attract investment. At the same time the fringes of
industry and academia may harbor the real innovators that should be funded to transform
R&D. Both governments and pharmas could use software like Collaboration Finder (25)
to find the best researchers to fund and collaborators to work with on strategic priorities.
This would enable NIH to fund continuous innovation, rather than rebuilding academia in
8
9. the shape of big pharma. Disruption of the pharmaceutical industry may begin by a
fundamental rethink of how to reward collaborative researchers in any organization.
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9
10. 32. W3C. http://www.w3.org/.
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46. Conflicts of Interest: SE Consults for Collaborative Drug Discovery and is on the
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employee of CollaborationFinder.
10
11. Table 1. North American small molecule databases containing FDA approved drugs
Database Funding Content and details URL
name
PubChem NIH >30M molecules includes http://pubchem.ncbi.nlm.nih.g
FDA approved drugs ov/
NPC NIH ~10,000 compounds http://tripod.nih.gov/npc/
Browser includes FDA approved
drugs
ToxCast EPA >1000 compounds includes http://epa.gov/ncct/toxcast/
some drugs and drug like
molecules
DailyMed FDA >31,942 labels – many http://dailymed.nlm.nih.gov/da
labels for the same drug ilymed/about.cfm
ChemIDplus NIH > 295,000 structures http://chem.sis.nlm.nih.gov/ch
including many FDA small emidplus/
molecule approved drugs
DrugBank Canadian 6707 drug entries including http://www.drugbank.ca/
1436 FDA-approved small
molecule drugs (this may be
underestimated).
11