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      <title>PHA60104 Principles of Drug Discovery and Development Aug 2018 by Yap Wei Hsum .</title>
      <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud</link>
      <description>The future of drug discovery</description>
      <language>en-us</language>
      <pubDate>2017-08-17 15:12:06 UTC</pubDate>
      <lastBuildDate>2025-12-22 12:32:52 UTC</lastBuildDate>
      <webMaster>hello@padlet.com</webMaster>
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         <title>Chan Le Roy</title>
         <author></author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/276129753</link>
         <description><![CDATA[<div><strong>Question 1</strong><br>The future trends of drug discovery and development are expected to increase<br><br><strong>Question 2<br>1st challenge: </strong>The high risk of failure<br><strong>2nd challenge:</strong> Extremely demanding in capital requirements and time<br><strong>3rd challenge:</strong> The increasing regulatory stringency that cause the approval of new drugs has become significantly more difficult</div>]]></description>
         <enclosure url="" />
         <pubDate>2018-08-29 06:19:07 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/276129753</guid>
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      <item>
         <title>Siau Yaw Wen</title>
         <author></author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/276848415</link>
         <description><![CDATA[<div><strong>Future Trends:</strong><br>New technology for analyzing chemical compounds and monitoring their effects will be developed, allowing drugs for treating or preventing more complex diseases to be discovered.</div><div><br><strong>Challenges:</strong></div><ol><li>High costs and long durations of drug trials.</li><li>Low success rate of drug candidates during clinical trials.</li><li>Technology and discovery methods no advanced enough to fully understand complex diseases or find the drugs to treat them.</li></ol>]]></description>
         <enclosure url="" />
         <pubDate>2018-08-31 10:43:42 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/276848415</guid>
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      <item>
         <title>Bilal Tahir</title>
         <author></author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/277185786</link>
         <description><![CDATA[<div>Future Trends:<br>As expected due to use of computer based program which allow us to bypass certain ordeal so we can assume more and more drugs will be discovered hence overall it will continue to progress and allow us to expand our research.<br><br>Challenges:<br>1) Expansive and time consuming.<br>2) due to over abuse of antibiotics we would have to come up with other alternatives as the dieasese are getting more complicated.<br>3) dependent upon extensive clinical trials.<br><br></div>]]></description>
         <enclosure url="" />
         <pubDate>2018-09-02 23:23:55 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/277185786</guid>
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      <item>
         <title>Wai Leong =)</title>
         <author>leewl0108</author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/278431889</link>
         <description><![CDATA[<div><strong>1.</strong>     <strong>What are the future trends of drug discovery and development?<br></strong><br></div><div>-        Computer-aided drug discovery (CADD) services across different stages of drug discovery, such as target identification, target validation, hit generation, hit-to-lead and lead optimization to bypass the random screening of billions of molecules across hundreds of biological targets in order to save cost and time</div><div>-        Identify ways to mitigate the risks associated with novel drug discovery programs to avoid failure</div><div>-        Various computational tools and services have emerged, enabling the selection, modeling, analysis and optimization of potential lead candidates</div><div>-        Human genetics is going to represent a core component of future drug discovery strategy to cut the cost of development in half.</div><div>-        The use of cloud technology and artificial intelligence to improve drug development efficiency</div><div>-       Expanding chemical space for drug discovery explorations</div><div>-       Targeting RNA with small molecules</div><div>-       New antibiotics discovery</div><div>-       Phenotypic screening</div><div>-       Organs (body)-on-a-chip</div><div>-       Bioprinting</div><div>-       High-throughput screening has undoubtedly emerged as a powerful lead-finding technology</div><div>-       A new trend is the growing of biopharmaceuticals, particularly monoclonal antibodies</div><div>-       Genotyping to individualize drug treatments<br><br><br>2<strong>.</strong>     <strong>What are the challenges of drug discovery and development in the future?</strong></div><div>-        Process of drug discovery is extremely demanding, both in terms of capital requirements and time</div><div>-        There is always a high risk of failure</div><div>-        The increasing regulatory stringency cause the approval of new drugs become significantly more difficult</div><div>-        Cost and length of time it takes to bring a therapy from discovery to commercialization</div><div>-        Balance the resource demands of drug discovery and development with manufacturing, marketing, selling and distribution</div><div>-       Information overload</div><div>-      Picking a viable target in a disease area</div><div>-      Disease complexity (Halting one pathway may not be sufficient for efficacy)</div><div>-      Competition for “validated targets” is high</div><div>-      Disease knowledge is sometimes outside of pharma walls</div><div>-      Access to Human or Phenotypic assays and reagents</div><div>-      Increasing complexity of drug discovery process<br><br></div>]]></description>
         <enclosure url="" />
         <pubDate>2018-09-06 14:10:11 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/278431889</guid>
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      <item>
         <title>Chong Jia Yii</title>
         <author></author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/278912496</link>
         <description><![CDATA[<div><strong>Future trends:</strong></div><ul><li>Produce blockbuster drugs</li><li>Big push into genetics and cut the time that takes to develop medicines</li></ul><div><br><strong>Challenges in future:</strong></div><ul><li>Drug discovering process is demanding capital requirements and time</li><li>High risk of failure associated</li><li>Expensive</li><li><br></li></ul><div><br></div>]]></description>
         <enclosure url="" />
         <pubDate>2018-09-07 15:50:50 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/278912496</guid>
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      <item>
         <title>Alicia Ng </title>
         <author></author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/279062690</link>
         <description><![CDATA[<div><strong>Future Trends:<br></strong><br></div><ul><li>Phenotypic Screening</li><li>&nbsp;Adoption of Artificial Intelligence&nbsp;</li><li>Targeting RNA with small molecules&nbsp;</li><li>Bioprinting</li></ul><div><br></div><div><strong>Challenges</strong></div><ul><li>Information overload where some are not useful</li><li>Competition for validated targets&nbsp;</li><li>Increase complexity in drug discovery methods&nbsp;</li><li>Lengthy, complex and costly process, entrenched with a high degree of uncertainty that a drug will succeed.&nbsp;</li><li>Unknown pathophysiology for many nervous system disorders makes target identification challenging.&nbsp;</li></ul><div><br></div><div><br></div>]]></description>
         <enclosure url="" />
         <pubDate>2018-09-08 08:01:25 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/279062690</guid>
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      <item>
         <title>Chong Jia En</title>
         <author></author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/280368783</link>
         <description><![CDATA[<div><strong>Future Trends:&nbsp;</strong></div><ul><li>Rise of biosimilars</li><li>rapid uptake of generic drugs</li><li>Phenotypic drug discovery&nbsp;</li><li>greater usage of genomics and proteomics</li></ul><div><br><strong>Challenges:</strong></div><ul><li>high cost to bring new drugs into the market</li><li>decrease in patent protection&nbsp;</li><li>increase in generic drugs&nbsp;</li><li>low clinical trials success rate</li><li>drug development is complex, lengthy, costly and with high degree of uncertainty in success rate</li></ul>]]></description>
         <enclosure url="" />
         <pubDate>2018-09-12 14:26:42 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/280368783</guid>
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         <title></title>
         <author></author>
         <link>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/280449256</link>
         <description><![CDATA[<div><strong>Dikshita  Ramkhalawon</strong><br><br>QUESTION 1 <br>technology will be used to analyze certain chemical compounds. in the future,more new and effective drugs may be manufactured that will be useful in the science field. there will be evolution of drugs, the discovery of new drugs will continue to progress that will be useful to prevent the expansion of certain harmful diseases. <br><br>QUESTION 2 <br> :- it is a lengthy, complex and costly process with a degree of uncertainty that the drug will actually succeed<br><br>:- Animal models often cannot recapitulate an entire disease or disorder.<br><br>:- lack of validated diagnostic and bio markers to detect and measure biological states.<br><br>  </div>]]></description>
         <enclosure url="" />
         <pubDate>2018-09-12 16:35:03 UTC</pubDate>
         <guid>https://padlet.com/weihsumyap1/ji6m1qvfzmud/wish/280449256</guid>
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