Unlock the Full Potential of Your Scientific Data
For years, life sciences organizations have struggled to gain insights efficiently from fragmented, siloed scientific data. The current state of scientific data diminishes productivity – forcing research and data scientists to spend countless hours searching for data, moving it to centralized systems of record, and preparing it for analysis. This slows discovery, development, and delivery of groundbreaking new therapeutics and adds innumerable risks. Life sciences organizations are now prioritizing initiatives to replatform to the cloud and optimize data for use with technologies that accelerate innovation, including analytics, artificial intelligence (AI), and machine learning (ML). Core to this optimization is making data FAIR (Findable, Accessible, Interoperable, and Reusable). In this whitepaper, you'll learn how your organization can finally unlock the full potential of your scientific data!

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The Buyer’s Guide for Search in Pharmaceutical
There’s no avoiding the truth: Getting pharmaceutical drugs to market is a long and expensive process with no guarantee of success. Deloitte estimates that the average cost of the R&D process is currently US 2.2 billion per drug, and it’s only getting more expensive. The drug discovery phase, involving the discovery of novel and innovative compounds, consumes about a third of that investment and takes 10 to 12 years.

Data is the fuel that powers the engine of a well-functioning pharmaceutical company. Data informs research and drives decision-making throughout the drug development process, whether that is during the selection of a target pathway, the confirmation of efficacy and safety through clinical trials, the delivery to market, or its ongoing monitoring.

So how do you drive innovation, accelerate research, and shorten drugs’ time-to-market when the amount of information you have to sift through is growing exponentially?

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Top 5 Cybersecurity Threats and Challenges to Pharmaceutical Businesses for 2022
Pharmaceutical companies are experiencing an unprecedented digital transformation. While digital transformation has helped to improve business continuity and business/manufacturing processes it has also expanded the number of cybersecurity attack vectors threatening pharmaceutical companies. Industry cybersecurity leader, Fortinet, has identified the “Top 5 Cybersecurity Threats and Challenges to Pharmaceutical Businesses for 2022” that security experts should address to protect IP and ensure data privacy and integrity.

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Best Practices Guide to Data Privacy in Clinical Trials
As life sciences companies grow, the regulatory compliance requirements and risks expand as well. These responsibilities extend beyond conventional health-related frameworks (e.g. GxP, HIPAA, etc.) into the realm of data privacy.

For high-growth institutions with limited resources & bandwidth, the question arises: what should you do?

In this document, we chronicle some of the regulations affecting the life sciences industry and share 5 activities to help your organization comply with these new and dynamic laws. Though not comprehensive, we hope they provide you with a right-sized approach for your organization.
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Mycoplasma Safety Testing in Pharmaceutical Products
Ensuring the safety of your products, and therefore the safety of patients, is a critical concern for the manufacturers of pharmaceutical products. Contaminated cell cultures and products have the potential to cause serious illness in humans. If discovered before shipment, contamination can create a significant delay in product release and increased production costs. This white paper provides an overview of mycoplasma testing and considerations to address when executing these studies.
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Slashing Your R&D Cost Can Be Easier Than You Think
This white paper examines the skyrocketing cost of drug development and provides step-by-step guidance for executing a successful fail fast strategy. In this quick read, you will learn about the top benefits of a fail fast methodology, how to use technology to improve research results, and you will get simple tips for getting started.
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De-Risking Drug Discovery with Applied BioMath Assess™, a New Early Feasibility Assessment Tool for Biotherapeutics
The steep cost of developing a new therapeutic to market. Early feasibility assessment (EFA) has proven to drastically improve the efficiency of pharmaceutical R&D and should be integrated into every drug R&D program. Applied BioMath Assess*, a new web-based application that provides the necessary models and analyses via an intuitive interface, makes this integration a reality.

*Patent pending

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The Sinequa Espresso Guide to Intelligent Search for the Health and Life Sciences Sector
Intelligent search is the oil that lubricates the gears of your organization. Intelligent search reduces friction, speeds up access, and provides the context you need to make informed decisions.
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Spot-on UV/Vis accuracy with Big Lunatic & Stunner
Verifying the performance of UV/Vis spectrometers is a necessary but time-consuming and labor-intensive step in the development of biologics workflows. Having confidence in the accuracy and precision of an instrument beforehand makes it easier to know the work of verification is worth your time. Big Lunatic and Stunner have always been perfect for anywhere needing fast, low-volume, and highly accurate quantification of proteins and nucleic acids, but now with certified reference materials and new software they’re ready to deliver performance verification quicker and easier.
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The Evolution and Importance of Biomedical Ontologies for Scientific Literature
The volume of scientific literature being published has increased dramatically in the digital age. Ontologies and taxonomies are important tools to help researchers retrieve and understand this overwhelming amount of scientific literature, but using and managing ontologies can be challenging in itself. In this paper, CCC teams up with SciBite to look at the history of biomedical classification and how these systems have evolved to address new technology and use cases. We’ll explain the difference between taxonomies and ontologies, and discuss the challenges and successes that come with adopting and managing ontologies.
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Get the whole story: combine Tm and Tagg with sizing and polydispersity on Uncle
Thermal ramp stability measurements (Tm and Tagg) are well-established methods for ranking proteins and formulations for stability. This data is critical for stability determinations, and ensures that researchers are focusing on winning constructs and formulations. While valuable, there is additional information that is not easily gleaned from Tm and Tagg) experiments.
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The Throughput Booster for Binding Interaction Screening – the waveRAPID® Kinetics Assay

Want to accelerate your drug discovery process?
Get more interactions in hours, not days with waveRAPID. In contrast to traditional kinetics measurements, waveRAPID generates a pulsating concentration profile by injecting the analyte at the same concentration, but multiple times. The reliable characterization of an interaction using a single pickup from a single well, avoiding the typical washing steps between injections, is a significant boost for screening applications.
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Controlled and Regulated Chemicals: Ensuring compliance in research and manufacturing
The ‘is this regulated?’ headache. Any industry that handles large amounts of chemicals needs to correctly identify and handle both controlled and regulated substances. In this white paper, we discuss some of these challenges and simple steps that can be taken to improve compliance, identify regulated chemicals and make compliance more robust.
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Fast-tracking Innovation in Pharma with the Power of Cloud Computing
COVID vaccines and the advent of genomics have been two recent game-changing developments in the Pharma industry. Technology in this industry has never been so closely coupled with results, and the new, rapidly developed mRNA-based COVID vaccines provide convincing evidence of this connection. Cloud computing is one the key technology areas that has accelerated innovation in areas such as drug discovery, clinical trials, and genomics. In this white paper, you’ll learn how a healthy cloud-enabled ecosystem, have unrealized potential to improve data quality and transform the Pharma industry.
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Labeling Best Practices for Biobanks
Biobanks collect and store a large number of specimens, all of which need to be accurately identified, tracked, and stored under extreme cryogenic conditions. Managing such a large inventory of samples requires durable cryo labels and a robust management and tracking software. Labeling Best Practices for Biobanks reviews the types of labels, tracking information, and label solutions recommended when storing valuable samples. These unique solutions are highlighted and expanded upon throughout the white paper. These recommendations are supported by ISBER’s guide detailing their recommendations for repositories and associated addendum focusing on cryogenic storage.
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Leveraging Years of Data on GPCRs for Transformative Drug Discovery
GPCRs, which play a role in most biological processes, remain one of the most vibrant fields for drug discovery. Years of data are increasingly being leveraged to overcome the complexity of GPCR biology and pharmacology and accelerate GPCR drug discovery. It is now possible to hope to rationally design drugs with optimal effects, thanks to a better understanding of the concept of functional selectivity. A growing volume of structural data also allows researchers to perform virtual screens with ever-increasing numbers of compounds and suggest new small molecule candidates in mere hours instead of months, allowing the exploration of a chemical space that seems infinite.
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Drug Discovery in a Post-Pandemic World: How to Reaccelerate Discovery Efforts
As the current global health crisis continues to unfold, the need for innovation in life sciences and healthcare has never been more pressing. But many researchers and scientists have been forced to slow their progress as a direct result of pandemic-related public health concerns. In this guide, learn actionable steps biotech and pharma Bio-IT leaders can take to mitigate disruptive risks and remain competitive within this forever-changed landscape.
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Is FDA Compliance Purgatory in the Cloud?
Is the barrier of regulatory compliance keeping the life sciences industry from progressing to modern systems? And if it is, does it need to? Digital transformation largely depends on an organization's ability to adapt to modern platforms and systems, one of those being the cloud. However, with the FDA's strict compliance regulations, is it possible for life sciences organizations to effectively maintain compliance in a cloud environment? In this complimentary ebook, we'll explore: Where the FDA is moving in regard to regulatory compliance — and where they've been. The advantages, disadvantages, and opportunities of the cloud in regard to life sciences organizations. What factors the FDA recommends for regulated parties to consider when determining the suitability of outsourced electronic services, especially in cloud computing.
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Making Digital Transformation in the Lab a Reality
Are labs keeping up with innovation? The pace of innovation in life sciences is accelerating, and significant investment needs to be made for the laboratory to keep up. The priority? Transforming labs to become digitally enabled, globally connected powerhouses capable of breakthrough innovation at scale. And yet, Accenture research found that, of 128 industry leaders surveyed, 40% had not embarked on applying digital to research and development or quality control labs. Read our report
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Semantic Search: From Big Data to Smart Knowledge
The term ‘big data’ seems old school now that ‘machine learning’, ‘deep learning’ and emerging concepts such as ‘edge AI’ are the hypes of the day. However, despite our general familiarity with the concept of big data, challenges related to data-driven decision making still remain. Several key learnings have emerged over the last decade. The tension between the culture of generating massive volumes of data and the culture of applying that data to achieve meaningful outcomes is stronger than ever. How do we use our expensive data processing and analytics tools to generate actionable insights?
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4 Critical Reasons to Engage a Cloud Managed Services Provider
Cloud computing can accelerate research and development for life sciences organizations, but there are risks. Cloud Managed Service Providers can minimize the risk and cost of cloud computing, opening the opportunity to accelerate innovation.
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The Continuation of Medical Research while Participant Practice At-Home Isolation
With most of our daily activities on-hold or modified for the foreseeable future, medical research is a crucial pursuit that continues despite the current environment. Medical research is critical to detecting, diagnosing, reducing, and treating diseases – however, the global pandemic has the potential to disrupt and delay vital research.
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Who Owns the Data?
Patient data is increasingly valuable, but there are still questions about who owns that data. Currently, there’s no direct route for patients to share their own information with companies and organizations who want it. New technologies like cryptocurrency and blockchain may be changing that.
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Cloud Computing that's Ready for Life Sciences
Over the past decade the embrace of cloud computing by life sciences and healthcare has been comparatively slow. Concerns around security, performance, and regulatory compliance persuaded many organizations the downside risk was greater than the upside potential. Moreover, workable alternatives - based largely on internal data centers and private networks - were available and well understood. Not surprisingly, the cautious life sciences and healthcare (LS&H) community resisted change. Today, that picture has vastly changed.
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If You’re Moving to the Cloud, Who Are You Bringing with You?
Cloud, mobile, and social technologies are making it easier than ever for organizations and individuals to work productively. Anywhere, anytime access to applications and information inside and outside of the enterprise is becoming standard operating procedure.
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De-Identification 101
Big data and big privacy can go together. Safely and securely share health data information with the right strategy: de-identification. Learn everything there is to know about the process in Privacy Analytics’ white paper. De-identification takes data-masking to a whole new place–ensuring quality, granular data while minimizing risk of data breach and re-identification. HIPAA compliant, de-identification goes even further to protect sensitive information while maintaining data utility for secondary purposes.
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Using Cloud-Based Discovery Support
Quickly and easily discover valuable insights in regulatory intelligence across various disparate collections of unstructured content to support plans for new product development, to predict future performance, to advance scientific and manufacturing methods, and to improve the company’s quality and management.
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Making the lab of the future today’s reality
Get to the heart of what concepts such as ‘the lab of the future’ and ‘the paperless lab’ really mean while exploring the future of R&D. Examine the main drivers transforming the way researchers work and the response of the R&D enterprise software sector to the challenges of change.
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Accelerating the Pace of Discovery In the Age of Data Intensive Science
21st Century science and discovery is driven by Big Data and advanced collaboration. Genomic and biomedical researchers have long been challenged with finding effective ways of exchanging Big Data with distant colleagues. This whitepaper details how the 100G Internet2 Network and related solutions are solving challenges for the biomedical research and healthcare communities’ advanced technology and remote collaboration needs.
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Looking Forward: The Case for Intelligent Design (and Infrastructure) in Life Science Biologics R&D
This white paper highlights key issues facing biologics discovery researchers and product developers today and the new capabilities being brought forth by advances in science and technology. A discussion of how Dassault Systemes’ new BIOVIA Biologics Solution helps address these issues is included along with anticipated potential barriers to adoption.
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Data Virtualization: Agile Data Solutions for Life Sciences
This interactive eBook walks you through the technical and business efficiencies realized by Life Sciences companies using Data Virtualization. It includes real-life use cases that provide a glimpse on how Data Virtualization can make a winning difference to become agile, scalable and cost efficient, be it in Research & Discovery, Drug or Medical Devices product development or Customer Operations.
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How to Safeguard for PHI
Context is king when it comes to safeguarding Protected Health Information (PHI). As patients, we share many personal details with our care providers. Concerns over who has access to this information and how it may be used can cause us as much worry as our health issues. Effectively safeguarding PHI means knowing who will have access to the data, how it will be stored and what details it contains. In other words, its context for use.
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Taneja Group: Data-Aware Storage Category Report
Imagine data storage that’s inherently smart; it knows what type of data it has, how it’s growing, who’s using it or abusing it. Welcome to the new era of data-aware storage; it could not have come at a better time. This new data storage category offers tremendous real-time intelligence without impacting performance or quality of service.
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Considerations for Modernizing Scientific Compute Research Platforms
This white paper looks at the computing and storage needs in pharmaceutical research, disease research, and precision medicine environments and matches them to technologies modernizing their infrastructures.
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Transforming Large Scale Genomics and Collaborative Research
As sequencing data explodes in volume, the ability to transform this data into biomedical insights will require a cost-effective, open standards-based computational infrastructure that is built for extreme scalability. Infrastructure and tools will need to be optimized accordingly to execute, store and process massively large genomic workflows.
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HPDA for Personalized Medicine
Translational and precision medicine is pushing data analysis requirements to new levels. This white paper explores the factors driving analytic requirements and the benefits of a multi-disciplinary approach of applying high performance data analytics to the massive amounts of data generated in next-generation sequencing so organizations can speed their time to discovery to help identify the causes of diseases and allow personalized treatments.
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OpenStack for HPC: Meeting Your Varying HPC Requirements with a Flexible Private Cloud
It is no secret that more and more organizations are moving to cloud-based architectures. Many are using OpenStack, the open source cloud computing platform for this transition. And increasingly, OpenStack ecosystems being considered and used to execute High-Performance Computing (HPC) workloads.
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ProQinase: Syngeneic mouse models as a tool to study immune modulatory effects of cancer therapeutics
Every cancer treatment has the potential to induce a stimulatory or inhibitory effect on the immune response to a tumor. Scientific knowledge about the significance of the immune system for tumor eradication during conventional treatment is growing quickly, and an increasing number of immune-modulating drugs are entering clinical trials for cancer treatment. This necessitates investigating these drugs in the presence of an intact immune system, and syngeneic tumor models are the ideal tool to achieve this. In addition to our many xenograft mouse models, we established several syngeneic tumor models, which we thoroughly characterized with respect to immune phenotyping and response to immune checkpoint inhibition. Four of them are introduced in this white paper
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IBM and Accelrys Deliver Turnkey NGS Solution
Fast and affordable NGS is fundamentally transforming the healthcare and life sciences industries. By improving time-to-market for preventive and personalized medicine, companies can save millions of dollars in drug discovery and development costs while delivering innovative therapies. Accelrys running on IBM systems provides an optimal environment for the rapid extraction of biological meaning from NGS data. And deployment is simple with the preintegrated IBM Application Ready Solution for Accelrys based on joint reference architecture developed with Accelrys.
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An Infrastructure to Meet Today's Life Sciences Research Requirements
Due to the growing data volumes involved in life sciences research and the need for speedy analysis, traditional IT infrastructures – either monolithic symmetric multiprocessing systems or loosely integrated high performance computer (HPC) clusters -- do not fare well. The problem is that such infrastructures are hard to scale or struggle to deliver the needed performance, and as a result can be an obstacle to research progress and investigative success.
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SLIPSTREAM APPLIANCE: NGS EDITION - MIT's Ed DeLong Sifts Microbial Treasure Troves Using SlipStream
Deciphering how marine microbial communities in­uence the world’s energy and carbon budgets is the province of Ed DeLong1 , prominent metagenomics researcher at MIT and member of the National Academy of Sciences. Few scientists match DeLong’s animated eloquence when discussing the quest to understand lowly microbial “bugs” – a pursuit that today depends heavily on next generation sequencing (NGS), powerful computational tools, and submersible robots able to roam the sea.
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Bridging the gap between compliance and innovation
Success in medical device manufacturing requires continual innovation in order to deliver improvements in the quality of patient care. This in turn drives business revenue and profits. At the same time, device manufacturers need to comply with the extensive quality systems regulations as issued by the Food and Drug Administration (FDA) and other regulatory bodies and standards organizations.
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Comply or Perish: Maintaining 21 CFR Part 11 Compliance
The biggest challenges of Life Sciences companies today are maintaining a robust product pipeline and reducing time to market while complying with an increasing and evolving multitude of Federal and international regulations. In this paper, we discuss the particular requirements of rule 21 CFR Part 11 and describe how OpenText Regulated Documents built on OpenText Content Server – the leading collaborative knowledge management software from OpenText, enables Life Sciences companies to comply with 21 CFR Part 11.
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Enterprise Informatics: Key to Precision Medicine, Scientific Breakthroughs, and Competitive Advantage
Given their level of investment in data and data management systems, healthcare delivery and life sciences organizations should be deriving considerable value from their data. Yet most organizations have little to show for their effort; the capabilities of their systems are highly compromised, and the practice of precise, evidence-based medicine remains elusive. The fact that these institutions have spent many years collecting data and building infrastructure for so little return has, for many, become “the elephant in the room”—a painfully obvious and uncomfortable topic of conversation.
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OpGen's Whole Genome Mapping Tackling Sequencing's Unfinished Business
Important projects once deemed impractical are now within reasonable reach and modest sequencing studies are done in a few weeks. Consider the ambitious 1000 Genomes Project1 launched in January 2008 to develop a comprehensive resource on human genetic variation. In November 2012, the project successfully completed its first phase – publication of variation from 1092 human genomes – a remarkable feat.
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LIFE SCIENCES AT RENCI - Big Data IT to manage, decipher, and inform
This white paper explains how the Rennisance Computing Institute (RENCI) of the University of North Carolina uses EMC Isilon scale-out NAS storage, Intel processer and system technology, and iRODS-based data management to tackle Big Data processing, Hadoop-based analytics, security and privacy challenges in research and clinical genomics.
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Hadoop's Rise in Life Sciences
By now the ‘Big Data’ challenge is familiar to the entire life sciences community. Modern high-throughput experimental technologies generate vast data sets that can only be tackled with high performance computing (HPC). Genomics, of course, is the leading example. At the end of 2011, global annual sequencing capacity was estimated at 13 quadrillion bases and growing rapidly1 . It’s worth noting a single base pair typically represents about 100 bytes of data (raw, analyzed, and interpreted).
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Challenges in Next-Generation Sequencing
The goal of Next Generation Sequencing (NGS) is to create large, biologically meaningful contiguous regions of the DNA sequence—the building blocks of the genome—from billions of short fragment data pieces. Whole genome “shotgun sequencing” is the best approach based on costs per run, compute resources, and clinical significance. Shotgun sequencing is the random sampling of read sequences from NGS instruments with optimal coverage. NGS coverage is defined as: Number of reads x (Read Length/Length of Genome). The number of reads is usually in the millions with the read length and length of genome quoted in base pairs. The length of the human genome is about 3 billion base pairs.
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Heterogeneous Computing in the Cloud: Democratizing Compute Resources for Life Sciences
The combination of heterogeneous computing and cloud computing is emerging as a powerful new paradigm to meet the requirements for high-performance computing (HPC) and data throughput throughout the life sciences (LS) and healthcare value chains. Of course, neither cloud computing nor the use of innovative computing architectures is new, but the rise of big data as a defining feature of modern life sciences and the proliferation of vastly differing applications to mine the data have dramatically changed the landscape of LS computing requirements.
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Reap the Benefits of the Evolving HPC Cloud
Harnessing the necessary high performance compute power to drive modern biomedical research is a formidable and familiar challenge throughout the life sciences. Modern research-enabling technologies – Next Generation Sequencing (NGS), for example – generate huge datasets that must be processed. Key applications such as genome assembly, genome annotation and molecular modeling can be data-intensive, compute intensive, or both. Underlying high performance computing (HPC) infrastructures must evolve rapidly to keep pace with innovation. And not least, cost pressures constrain both large and small organizations alike.
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High Performance and High Throughput
High-throughput genome sequencing, or nextgeneration genome sequencing (NGS), is being driven by the high demand for low-cost sequencing. NGS parallelizes the sequencing process, producing thousands or millions of sequences at once [1,2]. The latest NGS sequencers from 454 Sequencing [3], Solexa (Illumina) [4] and Applied BioSystems (SoLiD) [5] now routinely produce terabytes (TB) of data. For example, the SoLiD 5500xl produces in one run (~7days) over 4TB of data. With additional overheads of reference genome storage/access, and type of analysis to be done, there is a requirement for cost effective, high performance and high throughput clusters and storage to handle these tasks. The ultimate goal is to bring down the cost of genome sequencing to within $1K with a turn-around time of one week, enabling personalized genomics medicine to become commonplace. Currently, times vary from one week to four weeks depending on the cluster infrastructure, and costs are still high. Figure 1 below shows the current associated cost structure for a human-sized gen
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Optimizing Early Phase Oncology Clinical Trials
Oncology products continue to dominate the global therapeutics market. With anticipated continued strength, this therapeutic area will reach approximately $75 billion in global spending by 2015. Further, anticancer drugs continue to be the leading research therapeutic, with 672 oncology drugs in development.
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Translational Research 2.0 by Chris Asakiewicz PhD
The World Wide Web has revolutionized how researchers from various disciplines collaborate throughout the world. In the Life Sciences, interdisciplinary approaches are becoming increasingly powerful as a driver of both integration and discovery. Data access, data quality, identity, and provenance are all critical ingredients to facilitate and accelerate these collaborative enterprises, and it is in the area of Translational Research where Web 2.0 technologies promise to have a profound impact—enabling reproducibility, aiding in discovery, and accelerating and transforming medical and healthcare research across the healthcare ecosystem. However, integration and discovery require a consistent foundation upon which to operate. A foundation capable of addressing some of the critical issues associated with how research is conducted within the ecosystem today and how it should be conducted for the future.
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BIG DATA: Managing Explosive Growth The Importance of Tiered Storage
The reasons organizations are collecting and storing more data than ever before is because their businesses depend on it. The trend toward leveraging Big Data for competitive advantage and to help organizations achieve their goals means new and different types of information—website comments, pharmaceutical trial data, seismic exploration results, to name just a few—is now being collected and sifted through for insight and answers.
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The Swiss Institute of Bioinformatics Reduces Cost of Multi-Petabyte Storage by 50% with Quantum StorNext Software
When The SIB Swiss Institute of Bioinformatics was faced with spiralling data growth arising from next generation sequencing, it deployed a hierarchical storage management (HSM) solution centered on Quantum StorNext data management software and HP hardware. This provided high performance file sharing and data protection and reduced SIB’s total cost of storage by 50%.
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From Convergence Vision to Reality
A detailed discussion of the technology used in Perceptive MyTrials is beyond the reach of a short paper, but a substantive overview is instructive. MyTrials is SaaS delivered and based on a federated architecture that emphasizes standards (XML, SAML, BRIDG, etc.) where practical, openness for third-party integration, data virtualization techniques that minimize data movement and speed performance, and agile development techniques to accommodate rapid change.
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Instrument Integration: Common Pitfalls and Novel Approaches
Integrating instruments is a hassle. But as labs seek to improve efficiency, compliance, and data quality, integrating instruments with informatics systems is an obvious investment. This white paper takes a closer look at the traditional options for instrument integration, as well as emerging cloud-enabled technologies that are easier to deploy and manage.
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Wiley Chem Planner Synthesis Solved
In this case study, Wiley ChemPlanner was applied to help a chemist identify alternative and shorter synthetic routes to target molecules. Options that were not known to the chemist and would likely not have been identified by searching the literature with traditional search tools were found. ChemPlanner thus helped the chemist to increase the efficiency of the synthesis development process by reducing the time and resources spent.
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Lab Workstation Automation
“You have to walk before you can run.” You’ve heard it in other contexts, but is it true in laboratory automation? Our experience indicates that it is. We’ve also learned that trying to automate everything at once is a prescription for disaster. Like the human progression from crawling to walking to running, labs that choose to automate do it most successfully in a logical sequence of steps, or phases, each one building on the foundation of the last.
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Fast and Accurate Sample ID in the Lab
Laboratories—whether clinical, analytical, or pure research—can scarcely automate today without barcodes. While other technologies may someday offer more cost-effective ID techniques, barcodes are generally the best technology for positive sample identification within modern labs.
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Acquiring Scientific Content: How Hard Can It Be?
SO CLOSE AND YET SO FAR. Is that how many documents seem to you? Getting what you want—when, where, and how you want it—can be a real pain. That’s why we created this concise guide to getting around the obstacles that stand between you and the information your organization needs. Learn how to: Avoid busting the budget on expensive subscription access, Acquire even the most elusive content with equal ease, and Slash delivery turnaround time from days to minutes.
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Protein stability assessment after automated buffer exchange
Buffer preparation, exchange and sample concentration for a formulation screen can take 2–4 days of a scientist’s time. While many labs have developed strategies to streamline formulation development, it’s still relatively manual and requires significant resources which can limit the number of formulations evaluated. Learn how to eliminate these bottlenecks by reading this whitepaper.
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The Safe Harbor vs Statistical One
To leverage PHI for secondary purposes, an understanding of the different de-identification mechanisms is required. Under the HIPAA, there are two methods for de-identification: Safe Harbor and the Statistical Method (otherwise known as Expert Determination). While both are under HIPAA’s privacy rule, they are not the same. Understanding the difference between these two methods will ensure success when unlocking health data.
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How to Select an ELN for Biology R&D
With drug discovery trending towards heightened costs, complexity, and collaboration, ensuring that your R&D organization has the best tools possible for documenting research is more important than ever. But for many scientists and informatics professionals, the electronic lab notebook (ELN) sourcing and evaluation process is complex and murky. It involves a lot of moving parts without a clear market standard to assess against, but the stakes are clear. Implementing an ELN-centric informatics solution is an integral part of ensuring that an R&D organization runs at full efficiency, but if the wrong ELN is implemented, it runs the risk of generating inefficiency, a lack of adoption, and insufficient integration with other systems.
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Accelerating your process optimization: sampling from reactions in-progress means better decisions in less time
The Optimization Sampling Reactor (OSR) from Unchained Labs is a proven automation tool that lets researchers study reaction kinetics, track conversion and impurity formation and determine the reaction end-point over short and long time scales, all without running extra reactions or having to use large amounts of material. You can get the right data and enough of it, which allows you to optimize processes faster while increasing scale up success. In this application note, we demonstrate how the OSR technology was used in our search for the best chemistry for OSR validation.
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Reducing Cycle Time with Digital Transaction Management
This eBook provides best practices to drive digital adoption in life sciences, including how you can: Reduce Cycle Time, Improve Trial Enrollment and Informed Consents, Simplify Operations & Approvals.
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DocuSign Life Science Solutions for Regulated Life Science Operations
The pressure has never been greater for life science organizations to shorten the development cycle for new drugs and devices — and to do so while cutting costs and complying with industry regulations like 21 CFR Part 11 and Annex 11. DocuSign makes it easier and more efficient for you to adopt digital approvals, agreements and processes for regulated life science use cases. To fuel your digital success, we have outlined DocuSign’s options to help you implement e-signature and digital platform solutions while adhering to life science regulations: DocuSign Life Sciences Module, DocuSign Signature Appliance, Third Party Industry Credentials and Process Validation
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Solving the Knowledge Management Puzzle in Biopharma
If yours is a small- or medium-sized biopharma business, we can help you putting the pieces together. Learn the secrets of top knowledge management experts who will show you how to: Search, discover, acquire and manage knowledge in new ways, eliminate jumping through hoops to ensure copyright compliance, and monitor the biopharma landscape for safety and competitive edge.
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Why You Shouldn’t Limit Yourself To Blast in IP Searches
If you’re looking to protect your own sequences or want to make sure you’re not infringing on anyone else’s IP then you have to rely on a sequence search algorithm to provide you with a complete list of correct matches. BLAST, the most commonly used sequence comparison algorithm in biology, is an obvious and popular choice. What most people do not realize is that BLAST is not easy to control and not always up to the task. It’s not di­fficult to imagine how incorrect and incomplete search results can lead to wrong conclusions and -awed business decisions. Here we take a look at the most important issues with BLAST and propose a solution.
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High-performance File System Solutions for Hybrid Cloud Infrastructures
Bridge existing data centers and AWS resources by building a Hybrid Cloud. While the cloud may be the future of IT infrastructure, your business runs solidly on an owned data center foundation today. Shifting application workloads to the cloud can be complex and needs to be well-planned to avoid disruption and havoc to short-term business goals. In this ebook, you’ll learn how Avere Systems and AWS work together to support hybrid infrastructures that allow a phased approach to adoption. Workloads and resources can be used as they make sense with Avere’s high-performance data access layer that overcomes common challenges for enterprise-scale architectures.
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Don’t Get Data Stuck in Email
In a time of increased outsourcing and diversified industries working together for a common purpose, an electronic solution for unified data management is more important than ever. The IDBS E-WorkBook Cloud platform has been designed from the ground up to behave, look, and feel like a single, seamless application. This provides a superior user experience and eliminates the need to maintain complex integrations between systems from different vendors - allowing users to drastically simplify the deployment process and improve team collaboration for better results.
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Case Study: How a Leading Cancer Research Center is Building a World-Class Hybrid Infrastructure
One of the leading cancer research centers in the world wanted to reduce on-premises infrastructure and leverage Amazon Web Services (AWS) for compute and long-term storage. But they needed a way to transition their Network-attached storage (NAS) workloads to AWS without disrupting important research. The Avere Hybrid Cloud NAS solution offered a way to help them migrate data to AWS at a pace that worked for them without excessive costs, latency or security concerns. With the Avere and AWS solution, this organization was able to access the benefits of the cloud without excessive latency or disruptions.
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