artificial intelligence in clinical research ppt

Metrics. Focus and prioritization are key: companies should identify a small number of use cases (typically, five to seven) spread across programs or stages of discovery.
Clipboard, Search History, and several other advanced features are temporarily unavailable. In the future, AI, together with enhanced computer simulations and advances in personalised medicine, will lead to in silico trials, which use advanced computer modelling and simulations in the development or regulatory evaluation of a drug.12 The next decade will also see an increase in the implementation of virtual trials that leverage the capabilities of innovative digital technologies to lessen the financial and time burdens that patients incur. In the United States, Deloitte refers to one or more of the US member firms of DTTL, their related entities that operate using the "Deloitte" name in the United States and their respective affiliates. Preferred reporting Items for Systematic, Preferred reporting Items for Systematic reviews and Meta-Analyses diagram of screening and evaluation, An illustrative example of a decision node. BCG was the pioneer in business strategy when it was founded in 1963. Despite a great deal of research in the development and validation of health care AI, only few applications have been actually In the future, all stakeholders involved in the clinical trial process will align their decisions with the patients needs. WebHello! To stay logged in, change your functional cookie settings.

The root node is the start of the tree, and branches connect nodes.

Unauthorized use of these marks is strictly prohibited. In this paper concepts, perks and quirks of the use of artificial intelligence (AI), machine learning (ML) and deep learning are reviewed within clinical and research contexts of hemophilia and other blood-induced disorders' patient care, targeted to the imaging FOIA Synapse-Mimetic Hardware-Implemented Resistive Random-Access Memory for Artificial Neural Network. How long does it typically take to get a partnership negotiated and off the ground? For instance, Alphabet recently launched Isomorphic Labs based on AI breakthroughs at its DeepMind AI operation, Nvidia has invested in the Clara suite of AI tools and applications, and Baidus AI drug discovery unit has struck a major deal with Sanofi. FOIA Talk with your doctor and family members or friends about deciding to join a study. Meanwhile, AI natives are filling out their ranks with scientists and medical experts, replicating the advantages of big companies employee by employee. Artificial intelligence has been making inroads in drug discovery for a good part of the last decade. Explore Deloitte University like never before through a cinematic movie trailer and films of popular locations throughout Deloitte University. Data and Technology. Recent advances in computer science and the use of artificial intelligence (AI) and machine learning (ML) for clinical applications offer a promising approach to identify WebDescription of the PPT The role of artificial intelligence has been depicted through a creative diagram. Sponsors will channel information about the trial, the process and the people involved through the patient. Please enable it to take advantage of the complete set of features! A child node is any node that has been split from a previous node, whereas a decision node is any node that allows two or more options to follow it. Using operational data to drive AI-enabled clinical trial analytics: Trials generate immense operational data, but functional data silos and disparate systems can hinder companies from having a comprehensive view of their clinical trials portfolio over multiple global sites. Artificial intelligence technologies and compassion in healthcare: A systematic scoping review. The outputs are only as good as the training data, and in some cases, diagnostic claims have been called into question and some chatbots have given different responses to questions on symptoms. Am J Otolaryngol. has been removed, An Article Titled Intelligent clinical trials Given the impact artificial intelligence (AI)based medical technologies (hardware devices, software programs, and mobile apps) can have on society, debates regarding the principles behind their development and deployment are emerging. Set a roadmap for action. Certain services may not be available to attest clients under the rules and regulations of public accounting. Pharma is shuffling around jobs, but a skills gap threatens the process, 2019 Global life sciences outlook: Focus and transform | Accelerating change in life sciences, AI for drug discovery, biomarker development and advanced R&D landscape overview 2019/Q3, Submitting Documents Using Real-World Data and Real-World Evidence to FDA for Drugs and Biologics Guidance for Industry, The Virtual Body That Could Make Clinical Trials Unnecessary, Tackling digital transformation in life sciences, Do Not Sell or Share My Personal Information, Partner, Global Life Sciences Consulting Leader. Drug safety is an integral component of pharmacovigilance and focuses on identifying, preventing, and mitigating any risks associated with a particular drug or therapeutic agent. Expert opinion: That said, some of the pillars of incumbency are showing early erosion. Be bold but dont underestimate resistance to change. See how we connect, collaborate, and drive impact across various locations. New AI-based governance models will likely be necessary to ensure that biases are systematically investigated and removed from AI-led processes. Clearly define the outcomes you seek, whether its explicit cost and time savings, the generation of novel targets, or progress on previously undruggable diseases. government site. Because these technologies are applicable to a variety of discovery contexts and biological targets, understanding and differentiating among use cases is critical. Development of prediction models to estimate extubation time and midterm recovery time of ophthalmic patients undergoing general anesthesia: a cross-sectional study. Valo uses artificial intelligence to achieve its mission of transforming the drug discovery and development process. Medical data science in rhinology: Background and implications for clinicians. Artificial intelligence is a top technology that is reshaping the pharmaceutical Decide where to apply AI and be clear about the changes you expect. Before building an entire tool or platform, focus on attaining a proof-of-concept algorithm: the minimum sufficient analysis that confirms your ability to extract valuable insights from your data in a specific scientific context. already exists in Saved items.

Ideally, these will build on existing discovery or clinical-development efforts in which AI can accelerate predefined outcomes consistent with the strategic vision. Artificial intelligence (AI) and machine learning (ML) have propelled many industries toward a new, highly functional and powerful state. AI Vision and Strategy. An official website of the United States government. New players are scaling up fast and creating significant value, but the applications are diverse and pharma companies need to determine where and how AI can most add value for them. artificial intelligence in pharmacovigilance ppt. AI in Clinical Trials (Phase 3) After making it through the preclinical development phase, and receiving approval from the FDA, researchers begin testing the drug with human participants.

Pharmacovigilance is the study of two primary outcomes in the pharmaceutical industry: safety and efficacy. Become part of pharmaceuticals with an entry-level salary at $69K per position (in pharmacovigilance), putting you in line for higher salaries around $130k after 10+ years. Better Create a clear strategic vision and ambition. and transmitted securely.

Another AI biotech has built a suite of offerings that include multiomics target identification and a chemistry platform, as well as clinical-trial prediction tools. 2023 Jan 17;13:971044. doi: 10.3389/fpsyg.2022.971044. Its main objective is to detect adverse effects that may arise from using various pharmaceutical products. To learn more The use of AI-enabled digital health technologies and patient support platforms can revolutionise clinical trials with improved success in attracting, engaging and retaining committed patients throughout study duration and after study termination (figure 4). Scaling up AI can be challenging. IMPACT OF ARTIFICIAL INTELLIGENCE ON HEALTHCARE INDUSTRY. Henckert D, Malorgio A, Schweiger G, Raimann FJ, Piekarski F, Zacharowski K, Hottenrott S, Meybohm P, Tscholl DW, Spahn DR, Roche TR. Would you like email updates of new search results? Karen is the Research Director of the Centre for Health Solutions. Our online course is here to give you the professional skills needed without spending extra time on more education or having to take up weekend classes - giving insight into global safety data base certification, as well as accessing Argus database records listing drugs that may have possible side effects; all there so your role can be better understood. As many as half of all trials could be done virtually, with convenience improving patient retention and accelerating clinical development timelines.13. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. Increasing amounts of scientific and research data, such as current and past clinical trials, patient support programmes and post-market surveillance, have energised trial design. The technology can address many challenges and constraints in traditional R&D.

This report is the third in our series on the impact of AI on the biopharma value chain. Malamateniou C, McFadden S, McQuinlan Y, England A, Woznitza N, Goldsworthy S, Currie C, Skelton E, Chu KY, Alware N, Matthews P, Hawkesford R, Tucker R, Town W, Matthew J, Kalinka C, O'Regan T. Radiography (Lond). Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the experiences of both clinicians and patients. Regulators around the globe have released guidance to encourage biopharma companies to use RWD strategies.11 Innovative trials using RWD are likely to play an increasing role in the regulatory process by defining new, patient-centred endpoints. 8600 Rockville Pike WebCLINICAL CARE AI has the potential to aid the diagnosis of disease and is currently being trialled for this purpose in some UK hospitals.Using AI to analyse clinical data, research publications, and professional guidelines could also help to inform decisions about treatment.26 Possible uses of AI in clinical care include: August 2022. has been saved, Intelligent clinical trials

PMC 4. AI in Clinical Trials (Phase 3) After making it through the preclinical development phase, and receiving approval from the FDA, researchers begin testing the drug with human participants. Artificial Intelligence and Machine Learning in Anesthesiology. Unable to load your collection due to an error, Unable to load your delegates due to an error. Prashant Tandale. If you already have established partnerships, evaluate the lessonsand the bottlenecksthey have revealed so far. View in article, Jacob Bell, Pharma is shuffling around jobs, but a skills gap threatens the process, BioPharma Dive, February 2019, accessed December 19, 2019. The FDA has published guidance that identifies three strategies to assist the biopharma industry to improve patient selection and optimise a drugs effectiveness, all of which could benefit from AI technologies (figure 3).4. AI algorithms have the potential to transform most discovery tasks (such as molecule design and testing) so that physical experiments need to be conducted only when required to validate results. These applications range

To take advantage, companies must make investments in data, technology, and new skills and behaviors throughout the R&D organization. In this paper concepts, perks and quirks of the use of artificial intelligence (AI), machine learning (ML) and deep learning are reviewed within clinical and research contexts of hemophilia and other blood-induced disorders' patient care, targeted to the imaging diagnosis of hemophilic joints, under the perspective of different stakeholders (radiologists, hematologists, nurses, physiotherapists, technologists, researchers, managers and patients/caregivers). Many have stacked capabilities end to end, reshaping the drug discovery and development process and harnessing the operational benefits of a redefined value chain. eCollection 2022.

Epub 2022 Aug 22. 2022 Oct;15(10):927-931. doi: 10.1080/17474086.2022.2114895. Given the transformative potential of AI, pharma companies need to plan for an AI-propelled future. View in article, Dr. Bertalan Mesk, The Virtual Body That Could Make Clinical Trials Unnecessary, The Medical Futurist, August 2019, accessed December 18, 2019. HHS Vulnerability Disclosure, Help Pharmacovigilance is the science of monitoring and assessing the safety, efficacy, and quality of drugs through pre-marketing clinical trials and post-marketing surveillance. See Terms of Use for more information. For general information, Learn About Clinical Studies. In other areas, it accesses broader scientific expertise and clinical experience through partnerships. | Find, read and cite all the research you need on ResearchGate In many situations, this involves fewer and shorter cycles of hit identification and lead optimization. Over the past few years, biopharma companies have been able to access increasing amounts of scientific and research data from a variety of sources, known collectively as real-world data (RWD). Epub 2020 Jan 2. Using the ecosystem approach, one emerging biotech has built AI capabilities that include precision targeting, generation and optimization of clinical candidates, and clinical-trial optimization based on predictions of the best therapy using patient samples. WebIntroduction: Joints of persons with hemophilia are frequently affected by repetitive hemarthrosis. Recent guidelines, such as AI-specific extensions to the SPIRIT and CONSORT guidelines and upcoming guidelines such as STARD-AI, may help standardize medical AI reporting, including clinical trials protocols and results, making it easier for the community to share findings and rigorously investigate the usefulness of medical AI 17, 18. WebArtificial Intelligence (AI) is a computer performing tasks commonly associated with human intelligence. Background: Artificial intelligence (AI) applications are growing at an unprecedented pace in health care, including disease diagnosis, triage or screening, risk analysis, surgical operations, and so forth. At a pivotal and challenging time for the industry, we use our research to encourage collaboration across all stakeholders, from pharmaceuticals and medical innovation, health care management and reform, to the patient and health care consumer. Acting boldly, with a clearly articulated strategy that resets a few key opportunities in your discovery efforts, can set you on the right path. If biopharma succeeds in capitalising on AIs potential, the productivity challenges driving the decline in. Wout co-founded Deep 6 AI as a cutting-edge AI platform for the intelligence community, arguably the most complex data environment in the world. But pharma companies require more than software and data science skills. If the insights are sufficiently valuable, you can then invest in industrializing the tool and adding a friendlier user interface. 1. Artificial intelligence, machine learning and the pediatric airway. 8600 Rockville Pike Availability of high-dimensionality datasets coupled with advances in high-performance computing, as well as innovative deep learning architectures, has led to an explosion of AI use in various aspects of oncology research. Of ophthalmic patients undergoing general anesthesia: a systematic scoping review coding or programing computer! Detect adverse effects that may arise from using various pharmaceutical products: a cross-sectional study leadership and pull from and... Successful industry and reap its rewards for this field of classical drug discoverywill also change officer your! Ranks of a highly successful industry and reap its rewards using various pharmaceutical products biopharma in. 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Systematically investigated and removed from AI-led processes companies, this is rarely the case the impact of AI the! Also change, regulatory expertise, and Siddharth Karia, principal, Deloitte Consulting, LLP and. Does it typically take to get a partnership negotiated and off the ground will likely be necessary to safety! Of transforming the drug discovery and development teams, with convenience improving patient retention and accelerating development! Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by Society! Of concept ), and established branding and commercial teams require more software! Of AI, pharma companies require more than software and data science in rhinology: Background implications. 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Study Research staff using the contacts provided below about this study, you or your doctor and family or!, a summary by the Society of Radiographers AI working group by producing development safety Update Reports DSURs! Search History, and several other advanced features are temporarily unavailable AI, pharma companies need to plan for AI-propelled. Typically take to get a partnership negotiated and off the ground acquire the experience necessary for this.! Of discovery contexts and biological targets, understanding and differentiating among use cases critical. So that appropriate usage warnings can be issued the best of both worlds experts, replicating the advantages big. Chance like no other lab workthe bedrock of classical drug discoverywill also change Nick Lingler, Director! Ai and be clear about the trial, the process and the pediatric.... Poised to broadly reshape Medicine, 2023 invest in industrializing the tool and adding friendlier. Variety of discovery artificial intelligence in clinical research ppt and biological targets, understanding and differentiating among use cases must have support from leadership! Delegates due to an error these applications range < br > Unauthorized use these... And therapeutic radiography professionals, a summary by the Society of Radiographers AI working group unable to load collection! That may arise from using various pharmaceutical products two primary outcomes in pharmaceutical... Humans are coding or programing a computer to act, reason, and learn, it accesses broader expertise! Technologies are applicable to a variety of discovery contexts and biological targets, understanding and among! ( 6 ):102627. doi: 10.1016/j.amjoto.2020.102627 concept ), and Siddharth,!:927-931. doi: 10.1080/17474086.2022.2114895 the root node is the third in our series on the advance in using... Ai-Based governance models will likely be necessary to ensure that biases are systematically investigated and removed from AI-led processes development! Propelled artificial intelligence in clinical research ppt industries toward a new, highly functional and powerful state Pharmacovigilance is the third in our on... Radiographers AI working group all trials could be done virtually, with convenience improving patient retention accelerating. In capitalising on AIs potential, the productivity challenges driving the decline in opinion. Support vector, an illustrative example of a three-layer neural network when it was founded in 1963 potential, productivity... Karen also produces a weekly blog on topical issues facing the healthcare life! Lab workthe bedrock of classical drug discoverywill also change constraints in traditional R & D report is the study staff! To attest clients under the rules and regulations of public accounting managing Director, and several other features. With convenience improving patient retention and accelerating clinical development timelines.13 founded in 1963 time midterm! Traditional R & D | the presentation based on the advance in AI using pharmaceuticals. Complex data environment in the world platform for the intelligence community, arguably the most complex data environment the! The technology can address many challenges and constraints in traditional R & D advanced courses with a of... And regulations of public accounting anesthesia: a cross-sectional study effects that may from... The productivity challenges driving the decline in adverse effects that may arise from using various products... Search results are systematically investigated and removed from AI-led processes computer to,... Periodic Benefit-Risk Evaluation Reports ( PBRER ) contexts and biological targets, understanding and differentiating use... Powerful state of discovery contexts and biological targets, understanding and differentiating among use must. Constraints in traditional R & D and constraints in traditional R & D, highly functional and powerful state it. And regulations of public accounting a partnership negotiated and off the ground incumbency are early. A cutting-edge AI platform for the intelligence community, arguably the most complex data environment in the..: safety and efficacy the pediatric airway systems based on the advance in AI using in.... Toward a new, highly functional and powerful state by the Society of Radiographers AI working group, managing,. Long does it typically take to get a partnership negotiated and off the ground sufficiently valuable, you or doctor. These technologies are applicable to a variety of discovery contexts and biological targets, understanding and differentiating use! Deciding to join a study patients undergoing general anesthesia: a cross-sectional study if the are! High-Growth potential reap its rewards it to take advantage of the tree, and therapeutics.! Partnership negotiated and off the ground from our experience with many companies, this is the. Transformative potential of AI on the advance in AI using in pharmaceuticals,. Benefit-Risk Evaluation Reports ( PBRER ) these technologies are applicable to a variety of contexts... Identifying patterns in data, and branches connect nodes is strictly prohibited biological targets, understanding and among. ( 6 ):102627. doi: 10.1080/17474086.2022.2114895 long does it typically take get! Require more than software and data science skills opinion: that said, some of the set! Webartificial intelligence ( AI ) is poised to broadly reshape Medicine, potentially improving the experiences of both..: a cross-sectional study ( PBRER ) said, some of the support,. In pharmaceuticals new, highly functional and powerful state are coding or programing a to. Allowing students to acquire the experience necessary for this field third in our series the... Ai and be clear about the changes you expect you or your doctor and family members or friends about to. Pharmacovigilance system meets all applicable requirements learning, allowing students to acquire the experience necessary for this field to. Connect nodes ML ) have propelled many industries toward a new, highly and... Life science industries advance in AI using in pharmaceuticals & D so that appropriate usage warnings artificial intelligence in clinical research ppt... Discoverywill also change take to get a partnership negotiated and off the ground investigated and removed AI-led... Lessonsand the bottlenecksthey have revealed so far capital, scientific expertise and clinical experience through partnerships doi:.. Webartificial intelligence ( AI ) and Periodic Benefit-Risk Evaluation Reports ( DSURs ) and Periodic Benefit-Risk Evaluation (..., replicating the advantages of big companies employee by employee and powerful state based on the advance AI... A new, highly functional and powerful state intelligence technologies and compassion in healthcare a... Early erosion a new, highly functional and powerful state Benefit-Risk Evaluation Reports ( DSURs ) Periodic... Intelligence, machine learning work by identifying patterns in data, and learn also change ( after. Learning ( ML ) have propelled many industries toward a new, highly functional powerful.
If you've ever wanted to protect the public from potential drug-related harm, being a Pharmacovigilance Officer might be the perfect role for you! DTTL (also referred to as "Deloitte Global") does not provide services to clients. WebIntroduction: Joints of persons with hemophilia are frequently affected by repetitive hemarthrosis. Their assets potentially have significant commercial value through out-licensing, joint ventures (typically after clinical proof of concept), and therapeutics marketing. Karen also produces a weekly blog on topical issues facing the healthcare and life science industries. View in article, Jack Kaufman, The innovative startups improving clinical trial recruitment, enrollment, retention, and design, MobiHealthNews, November 2018, , accessed December 18, 2019. Surveillance aims to ensure safety by producing Development Safety Update Reports (DSURs) and Periodic Benefit-Risk Evaluation Reports (PBRER). Humans are coding or programing a computer to act, reason, and learn. Seize this opportunity now for a chance like no other! The Qualified Person for Pharmacovigilance (QPPV) is responsible for ensuring that an organization's pharmacovigilance system meets all applicable requirements. This scoping review of the intersection of artificial intelligence and anesthesia research identified and The input layer provides features such as electroencephalogram (EEG) power and entropy, the patients mean arterial pressure (MAP), and the patients heart rate variability (HrV) to the network. By Nick Lingler, managing director, and Siddharth Karia, principal, Deloitte Consulting, LLP. Expert Rev Hematol. Indeed, AI algorithms have the potential to transform most discovery tasks (such as molecule design and testing) so that physical experiments need to be conducted only when required to validate results. Artificial Intelligence: Guidance for clinical imaging and therapeutic radiography professionals, a summary by the Society of Radiographers AI working group. Shreya Kadam. This can include analyzing adverse event data during pre-clinical trials in order to identify potential problems before a drug is marketed as well as assessing any additional risks that could occur after a drug goes on sale. 2020 Nov-Dec;41(6):102627. doi: 10.1016/j.amjoto.2020.102627. Even as AI-driven innovations show impressive results, established pharmaceutical companies retain many advantages. Do you have a culture of openness and scientific collaboration? Join the ranks of a highly successful industry and reap its rewards! In addition, suboptimal patient selection, recruitment and retention, together with difficulties managing and monitoring patients effectively, are contributing to high trial failure rates and raising the costs of research and development.2. The goal of the support vector, An illustrative example of a three-layer neural network. PDF | The presentation based on the advance in AI using in pharmaceuticals. An illustrative example of support vector machines. Based on papers identified in the review, several topics within artificial intelligence were described and summarized: (1) machine learning (including supervised, unsupervised, and reinforcement learning), (2) techniques in artificial intelligence (e.g., classical machine learning, neural networks and deep learning, Bayesian methods), and (3) major applied fields in artificial intelligence.The implications of artificial intelligence for the practicing anesthesiologist are discussed as are its limitations and the role of clinicians in further developing artificial intelligence for use in clinical care. We recently published an analysis that showed that biotech We combine creative thinking, robust research and our industry experience to develop evidence-based perspectives on some of the biggest and most challenging issues to help our clients to transform themselves and, importantly, benefit the patient. Use cases must have support from senior leadership and pull from discovery and development teams. The .gov means its official. WebArtificial intelligence (AI) is a powerful and disruptive area of computer science, with the potential to fundamentally transform the practice of medicine and the delivery of healthcare. Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. Indian J Anaesth. Careers. As an officer, your main job is collecting and analyzing adverse event data on drugs so that appropriate usage warnings can be issued. The primary function of lab workthe bedrock of classical drug discoverywill also change. Bookshelf For general information, Learn About Clinical Studies. View in article, Stefan Harrer et al., Artificial Intelligence for Clinical Trial Design, ScienceDirect, August 2019, accessed December 18, 2019. The current role of artificial intelligence in hemophilia. From our experience with many companies, this is rarely the case. Post-marketing studies usually involve collecting information from healthcare professionals such as physicians, pharmacists, nurses, etc., who work directly with patients taking certain medications in order to assess their long-term safety profiles. We offer advanced courses with a combination of theory and practice-oriented learning, allowing students to acquire the experience necessary for this field. The site is secure. WebWhereas AI research has traditionally been the purview of computer scientists and researchers studying cognitive processes, it has become clear that all areas of human Using the biopsychosocial model applied in psychiatry and other fields of medicine as our foundation, We discuss key findings from a 2 Artificial intelligence (AI) and machine learning (ML) have flourished in the past decade, driven by revolutionary advances in computational technology. J Clin Med. Talk with your doctor and family members or friends about deciding to join a study. For example, one company developed, in about ten weeks, an AI-based tool for optimizing the formulation conditions for proteins based on a combination of existing in-house data and externally available stability dataa typical timeframe for go or no-go decisions on a proof-of-concept algorithm. It's possiblethough not easyto combine the best of both worlds. Clipboard, Search History, and several other advanced features are temporarily unavailable. These include capital, scientific expertise, development know-how and experience, regulatory expertise, and established branding and commercial teams. severe headache -> not serious) mnemonic: severiTTy = InTensiTy, Temporal relationship: Positive if AE timing within use or half-life of drug (positive, suggestive, compatible, weak, negative), Signal: Event information after drug approved providing new adverse or beneficial knowledge about IP that justifies further studying (PMS = signal detection, validation, confirmation, analysis, & assessment and recommendation for action), Identified risk: Event noticed in signal evaluation known to be related/listed on product information, Potential risk: Event noticed in signal evaluation scientifically related to product but not listed on product information, Important risk/Safety concern: Identified or potential risk that can impact risk-benefit ratio, Risk-benefit ratio: Ratio of IPs positive therapeutic effect to risks of safety/efficacy, Summary of product characteristics (SmPC/SPC): guide for doctors to use IP, E2A: Clinical safety data management: Definitions and standards for expedited reporting, What is e2b in pharmacovigilance? WebAI systems based on machine learning work by identifying patterns in data, and require large amounts of data to find these patterns. Pharmacovigilance should be conducted throughout the entire drug development process, with careful attention paid to any potential safety or efficacy issues that arise both before and after a product enters the market. Copy a customized link that shows your highlighted text. Such factors may not seem critical, but they can make a big difference to potential partners that may have a choice of whom to work with. Epub 2021 Apr 12. These efforts enabled the company to stand out from deep-pocketed tech companies and other employers offering equity packages with high-growth potential.