{"id":15905,"date":"2021-06-21T20:05:25","date_gmt":"2021-06-21T14:35:25","guid":{"rendered":"https:\/\/coforge.site\/cigniti\/blog\/?p=15905"},"modified":"2021-12-29T14:53:15","modified_gmt":"2021-12-29T09:23:15","slug":"artificial-intelligence-ai-pharmaceutical","status":"publish","type":"post","link":"https:\/\/coforge.site\/cigniti\/blog\/artificial-intelligence-ai-pharmaceutical\/","title":{"rendered":"AI is here to stay. It&#8217;s time the Pharma industry woke up to it"},"content":{"rendered":"<p><span data-contrast=\"auto\">When discussing the future of any industry, it is difficult to avoid mentioning Artificial Intelligence (AI).<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">AI has revolutionized how scientists discover new treatments, combat diseases, and more in the pharmaceutical and biotech industries in the last five years.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">To help deliver safe, reliable pharmaceuticals to the market, the pharmaceutical industry has traditionally depended on cutting-edge technologies.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">AI is a term used in the pharmaceutical industry to describe the use of automated algorithms to do tasks that previously required human intelligence.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">With the latest outbreak, pharmaceutical companies are under more pressure than ever to produce treatments and vaccines to market as soon as possible.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">According to\u00a0<\/span><b><i><span data-contrast=\"auto\">Gartner<\/span><\/i><\/b><span data-contrast=\"auto\">, \u201c<\/span><b><i><span data-contrast=\"auto\">As far as enterprise artificial intelligence projects are concerned, the COVID-19 pandemic was just a minor bump in the road.\u00a024% of business and IT professionals surveyed said they increased AI investment during the pandemic, and 42% kept investment at the same level.\u00a0Driving current AI investment has been customer experience and retention, revenue growth, and cost optimization.\u00a0Those areas of focus are likely to continue as new projects are initiated in the post-pandemic business world, which will be rich with AI investment<\/span><\/i><\/b><span data-contrast=\"auto\">.\u201d<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">In the pharmaceutical and\u00a0customer\u00a0healthcare\u00a0businesses, AI and machine learning\u00a0(ML)\u00a0have proven\u00a0to be\u00a0crucial.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">COVID and the race to\u00a0discover\u00a0viable vaccines are\u00a0fostering\u00a0the use of AI and ML\u00a0in this pandemic.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"2\"><strong>Top-Level usage in the pharmaceutical and consumer healthcare industries\u00a0<\/strong><\/h4>\n<p><span data-contrast=\"auto\">The following are the top-level usages\u00a0in the pharmaceutical and consumer healthcare\u00a0businesses:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Prognostic Prediction<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211; One of the primary examples of this\u00a0subject\u00a0is\u00a0envisaging\u00a0an epidemic. ML and AI are also being used to track and predict disease outbreaks and seasonal illnesses around the world. Based on the projected intensity, a predictive forecast assists us in planning our supply chain to ensure that we have the correct inventory at the right time and in the right quantity.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Tailored\u00a0Treatment\/Interactive\u00a0Alteration\/Digital Therapeutics<\/span><\/b><span data-contrast=\"auto\">\u00a0\u2013 This can be used to\u00a0aid\u00a0and\u00a0recognize\u00a0people\u00a0in order to\u00a0deliver\u00a0primary\u00a0vision\u00a0into\u00a0a\u00a0illness\u00a0\u2013 such as gum disease \u2013 accurately classify cutaneous skin disorders, suggest primary treatment options with over-the-counter medication, and serve as an ancillary tool to improve clinicians&#8217; diagnostic accuracy, or improve educational and clinical decisions made by your child&#8217;s teacher.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Drug\u00a0Detection\u00a0and Manufacturing<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211;\u00a0It\u00a0helps\u00a0in the initial screening of medicinal compounds\u00a0for\u00a0the projected success rate based on biological parameters in drug discovery and manufacturing. RNA and DNA\u00a0are quickly measured. Precision medicine, also known as next-generation sequencing, aids in the identification of new pharmaceuticals and\u00a0personalized\u00a0treatments for particular patients.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Diagnosis\/Identify diseases<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211; This can include everything from oncology to COVID to ocular degeneration.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"1\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Clinical Trials<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211; Recognizing the best contender for the study based on their medical history, clinical conditions, and other characteristics, as well as infection rates, demography, and ethnicity to represent the individuals who will be most affected.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">We\u00a0see AI\u00a0and\u00a0ML being used in a variety of areas for\u00a0pharmaceutical\u00a0and\u00a0healthcare firms, including\u00a0Supply Chain, Customer Service,\u00a0Martech, AdTech,\u00a0and sales.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">While the top-level usage of AI in the pharma industry is huge, larger establishments face a few challenges while adopting AI.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"2\"><strong>Challenges in adopting AI at larger enterprises\u00a0<\/strong><\/h4>\n<p><span data-contrast=\"auto\">The following are some of the major obstacles to AI adoption in larger\u00a0organizations:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Data Challenges<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211; Data quantity and quality\u00a0&#8211;\u00a0A training data set containing a minimum of 2 to 3 years of historical data is required for every machine learning model to perform effectively. Due to mergers and acquisitions, prior data management, or the lack of a prior source of data, this is the most crucial difficulty we find in large enterprises.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Challenges with Skills<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211; Finding the correct resource with the right background might be difficult. We have a limited pool of data science experts in the market, which causes delays in hiring and training them to grow many AI initiatives.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">According to\u00a0<\/span><b><i><span data-contrast=\"auto\">Erick\u00a0Brethenoux<\/span><\/i><\/b><span data-contrast=\"auto\">, research vice president at\u00a0<\/span><b><i><span data-contrast=\"auto\">Gartner<\/span><\/i><\/b><span data-contrast=\"auto\">,\u00a0&#8220;<\/span><b><i><span data-contrast=\"auto\">The biggest misconception in the journey to successfully scaling AI is the search for &#8216;unicorns,&#8217; or the perfect combination of AI, business and IT skills all present in a single resource. Since this is impossible to fulfill, focus instead on bringing together a balanced combination of such skills to ensure results<\/span><\/i><\/b><span data-contrast=\"auto\">.\u00a0<\/span><b><i><span data-contrast=\"auto\">AI talent is multiple things, and business professionals, whether they consider themselves at risk for AI-driven obsolescence or not, should consider training in some way that makes them valuable for a future of automated work<\/span><\/i><\/b><span data-contrast=\"auto\">.\u201d<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Commercial\u00a0Value<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211; Larger companies are having difficulty demonstrating the business value of AI\u00a0programs. We&#8217;d like to deploy more cognitive services based on chatbots, for example. Adaptability, on the other hand, is insignificant, making it difficult to demonstrate the worth of such\u00a0endeavors.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Explainability<\/span><\/b><span data-contrast=\"auto\">\u00a0&#8211;\u00a0Many &#8220;black box&#8221; models result in a conclusion, such as a forecast, but no explanation. You&#8217;re not likely to challenge the system&#8217;s conclusion if it coincides with what you already know and believe is correct. But what if you have a disagreement? You&#8217;re curious as to how the choice was reached. In many circumstances, just making a decision isn&#8217;t enough. When it comes to their patients&#8217; health, doctors cannot rely only on the system&#8217;s recommendations.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Local interpretable model-agnostic explanations\u00a0(LIME)\u00a0is\u00a0one method for increasing model transparency.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">If AI determines that a patient has the flu, it will also reveal which data points were used to make that determination: sneezing and headaches, but not the patient&#8217;s age or weight, for example.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">When we&#8217;re provided the reasoning behind a conclusion, it&#8217;s much easier to determine how much we can trust the model.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"2\"><strong>Changing the Pharmacy Industry&#8217;s Future\u00a0<\/strong><\/h4>\n<p><span data-contrast=\"auto\">The application of AI allows pharmacists to play a more active role in patient care, which is critical as value-based care models continue to dominate the health-care industry.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Managing medicine inventories can be overwhelming for pharmacists.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">According to\u00a0<\/span><b><i><span data-contrast=\"auto\">McKinsey<\/span><\/i><\/b><span data-contrast=\"auto\">, \u201c<\/span><b><i><span data-contrast=\"auto\">Artificial intelligence is here to stay. Machine Learning and Big Data in the pharmacy and medical space might be worth $100 billion each year. Although some remain wary of AI&#8217;s promise, it&#8217;s evident that the pharmaceutical business is uniquely positioned to benefit and grow as a result of its implementation<\/span><\/i><\/b><span data-contrast=\"auto\">.\u201d<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Despite the fact that pharmacists are highly trained\u00a0in patient\u00a0care, they are frequently forced to function as de facto supply chain experts in order to keep their hospitals\u00a0stocked with the pharmaceuticals\u00a0they require.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Pharmacists can focus their efforts on patient care with the use of artificial intelligence, as some states have\u00a0recognized\u00a0in an official capacity.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<h4 aria-level=\"2\"><strong>Conclusion\u00a0<\/strong><\/h4>\n<p><span data-contrast=\"auto\">While leveraging AI for testing apps for quality, enterprises may face multiple challenges,\u00a0such as identifying the exact use cases, lack of awareness about what really needs to be done, verifying the app\u2019s\u00a0behavior based on the data that has been input, testing apps for functionality, performance, scalability, security, &amp; more.\u00a0<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Cigniti\u2019s\u00a0extensive experience in the use of AI, ML, &amp; analytics helps enterprises improve their automation frameworks &amp; QA practices.\u00a0Cigniti\u00a0provides <a href=\"https:\/\/www.cigniti.com\/services\/ai-based-application-testing\/?utm_source=blog&amp;utm_medium=hyperlink&amp;utm_campaign=AItesting\" target=\"_blank\" rel=\"noopener\">AI\/ML-led testing<\/a> and <a href=\"https:\/\/www.cigniti.com\/services\/performance-engineering\/?utm_source=blog&amp;utm_medium=hyperlink&amp;utm_campaign=PerformanceEngineering\" class=\"broken_link\" target=\"_blank\" rel=\"noopener\">performance engineering services<\/a> for your QA framework through implementation of its next gen IP, <a href=\"https:\/\/www.cigniti.com\/blueswan?utm_source=blog&amp;utm_medium=hyperlink&amp;utm_campaign=Blueswan\" target=\"_blank\" rel=\"noopener\">BlueSwan<\/a>&#x2122;.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">With a strong focus on AI algorithms for test suite optimization, defect analytics, <a href=\"https:\/\/www.incight.ai\/?utm_source=blog&amp;utm_medium=hyperlink&amp;utm_campaign=cigniti-blog\" target=\"_blank\" rel=\"noopener\">customer sentiment analytics<\/a>, scenario traceability, integrated requirements traceability matrix (RTM), rapid impact analysis, comprehensive documentation and log analytics, at\u00a0Cigniti, we have established a 4-pronged AI-led testing approach that includes:<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Discover<\/span><\/b><span data-contrast=\"auto\">\u00a0\u2013 Smart asset creation using data repositories including defects, tickets, logs etc. for analysis.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Learn<\/span><\/b><span data-contrast=\"auto\">\u00a0\u2013 Identify relationships between test assets such as defects and software requirements for insights.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Sense<\/span><\/b><span data-contrast=\"auto\">\u00a0\u2013 Predict occurrence of an incident, impact, and likelihood led by analytics and insights.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Respond<\/span><\/b><span data-contrast=\"auto\">\u00a0\u2013 Respond to an incident, input the resolution and results for continuous learning.<\/span><span data-ccp-props=\"{&quot;134233279&quot;:true,&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">Use our expertise in defect predictive analytics and test execution to ensure 100% test coverage for your AI-based applications.<\/span><span data-ccp-props=\"{&quot;201341983&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:259}\">\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>When discussing the future of any industry, it is difficult to avoid mentioning Artificial Intelligence (AI).\u00a0 AI has revolutionized how scientists discover new treatments, combat diseases, and more in the pharmaceutical and biotech industries in the last five years.\u00a0 To help deliver safe, reliable pharmaceuticals to the market, the pharmaceutical industry has traditionally depended on [&hellip;]<\/p>\n","protected":false},"author":20,"featured_media":15906,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2173],"tags":[3602,2475,3603,3599,3601,3600,1149,3598],"ppma_author":[3727],"class_list":["post-15905","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","tag-ai-at-larger-enterprises","tag-ai-for-testing-apps","tag-ai-in-pharma-industry","tag-ai-testing","tag-ai-led-testing-approach","tag-ai-ml-led-testing","tag-healthcare-software-testing","tag-pharmaceutical-testing"],"authors":[{"term_id":3727,"user_id":20,"is_guest":0,"slug":"cigniti","display_name":"About Cigniti (A Coforge Company)","avatar_url":{"url":"https:\/\/coforge.site\/cigniti\/blog\/wp-content\/uploads\/2024\/10\/Coforge-blog-Logo.png","url2x":"https:\/\/coforge.site\/cigniti\/blog\/wp-content\/uploads\/2024\/10\/Coforge-blog-Logo.png"},"author_category":"","user_url":"https:\/\/www.cigniti.com\/","last_name":"(A Coforge Company)","first_name":"About Cigniti","job_title":"","description":"Cigniti Technologies Limited, a Coforge company, is the world\u2019s leading AI &amp; IP-led Digital Assurance and Digital Engineering services provider. Headquartered in Hyderabad, India, Cigniti\u2019s 4200+ employees help Fortune 500 &amp; Global 2000 enterprises across 25 countries accelerate their digital transformation journey across various stages of digital adoption and help them achieve market leadership by providing transformation services leveraging IP &amp; platform-led innovation with expertise across multiple verticals and domains.\r\n<br>\r\nLearn more about Cigniti at <a href=\"https:\/\/www.cigniti.com\/\">www.cigniti.com<\/a> and about Coforge at <a href=\"https:\/\/www.coforge.com\/\">www.coforge.com<\/a>."}],"_links":{"self":[{"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/posts\/15905","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/comments?post=15905"}],"version-history":[{"count":0,"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/posts\/15905\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/media\/15906"}],"wp:attachment":[{"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/media?parent=15905"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/categories?post=15905"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/tags?post=15905"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/coforge.site\/cigniti\/blog\/wp-json\/wp\/v2\/ppma_author?post=15905"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}