{"id":7745,"date":"2020-06-05T11:44:07","date_gmt":"2020-06-05T11:44:07","guid":{"rendered":"https:\/\/www.kolabtree.com\/blog\/?p=7745"},"modified":"2020-06-05T11:55:08","modified_gmt":"2020-06-05T11:55:08","slug":"the-difficulties-in-clinical-trials","status":"publish","type":"post","link":"https:\/\/www.kolabtree.com\/blog\/ja\/the-difficulties-in-clinical-trials\/","title":{"rendered":"\u81e8\u5e8a\u8a66\u9a13\u306e\u96e3\u3057\u3055"},"content":{"rendered":"

\u79d1\u5b66\u7814\u7a76\u306f\uff0c\u8abf\u67fb\u5bfe\u8c61\u3068\u306a\u308b\u554f\u984c\u306b\u5bfe\u3059\u308b\u7b54\u3048\u304c\u660e\u78ba\u306b\u306a\u308b\u3088\u3046\u306b\uff0c\u591a\u6570\u306e\u5bfe\u7167\u5b9f\u9a13\u3084\u518d\u73fe\u5b9f\u9a13\u3092\u7528\u3044\u3066\u8a08\u753b\u3055\u308c\u308b\uff0e\u3057\u304b\u3057\uff0c\u81e8\u5e8a\u8a66\u9a13\u306e\u3088\u3046\u306a\u8907\u96d1\u306a\u5b9f\u9a13\u8a2d\u5b9a\u3067\u306f\uff0c\u7d50\u679c\u304c\u660e\u78ba\u3067\u306a\u3044\u3053\u3068\u304c\u591a\u304f\uff0c\u30c7\u30fc\u30bf\u306e\u5916\u633f\u306f\u4e0d\u53ef\u80fd\u3067\u3042\u308b[1]\u3002\u5b9f\u969b\uff0c\u591a\u304f\u306e\u81e8\u5e8a\u8a66\u9a13\u306f\u5341\u5206\u306b\u30c7\u30b6\u30a4\u30f3\u3055\u308c\u3066\u304a\u3089\u305a\uff0c\u7d50\u679c\u304c\u66d6\u6627\u3067\u3042\u3063\u305f\u308a\uff0c\u5f79\u306b\u7acb\u305f\u306a\u304b\u3063\u305f\u308a\u3059\u308b\u3053\u3068\u304c\u5831\u544a\u3055\u308c\u3066\u3044\u307e\u3059[1-3]\u3002\u4ed6\u306b\u3082\u3001\u9069\u5207\u306a\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u30b5\u30a4\u30ba\u306b\u5341\u5206\u306a\u60a3\u8005\u3092\u52df\u96c6\u3059\u308b\u3053\u3068 [4]\u3001\u52df\u96c6\u6642\u306e\u30d0\u30a4\u30a2\u30b9\u3084\u8a8d\u8b58 [2, 5]\u3001\u8a66\u9a13\u304b\u3089\u306e\u60a3\u8005\u306e\u96e2\u8131 [5, 6]\u3001\u900f\u660e\u6027\u306e\u6b20\u5982\u3001\u307e\u305f\u306f\u5341\u5206\u306a\u5c02\u9580\u5bb6\u306b\u3088\u308b\u30ec\u30d3\u30e5\u30fc\u306e\u6b20\u5982 [1, 7]\u306a\u3069\u306e\u554f\u984c\u306f\u3001\u8a66\u9a13\u3092\u6df7\u4e71\u3055\u305b\u3001\u660e\u78ba\u306a\u7d50\u8ad6\u3092\u5c0e\u304d\u51fa\u3059\u3053\u3068\u3092\u56f0\u96e3\u306b\u3059\u308b\u975e\u5e38\u306b\u73fe\u5b9f\u7684\u306a\u8981\u56e0\u3067\u3059\u3002\u3055\u3089\u306b\u3001\u533b\u85ac\u54c1\u306e\u691c\u8a3c\u306f\u3001\u901a\u5e38\u3001\u5e02\u5834\u3067\u306e\u627f\u8a8d\u5f8c\u3082\u7d99\u7d9a\u3055\u308c\u3001\u96c6\u56e3\u30ec\u30d9\u30eb\u3067\u306f\u3001\u7a00\u306a\u526f\u4f5c\u7528\u3084\u6a19\u7684\u5916\u306e\u52b9\u679c\u306f\u3001\u81a8\u5927\u306a\u30b5\u30f3\u30d7\u30eb\u6570\u3068\u9577\u3044\u671f\u9593\u3092\u304b\u3051\u3066\u521d\u3081\u3066\u89b3\u5bdf\u3055\u308c\u307e\u3059[8]\u3002\u00a0<\/span><\/p>\n

\u533b\u85ac\u54c1\u958b\u767a\u306e\u30d7\u30ed\u30bb\u30b9\u306f\u3001\u30d2\u30c8\u3067\u306e\u6709\u52b9\u6027\u3068\u5b89\u5168\u6027\u306e\u53b3\u683c\u306a\u30c6\u30b9\u30c8\u3092\u4f34\u3046\u305f\u3081\u3001\u9577\u304f\u3066\u5927\u5909\u306a\u3082\u306e\u3067\u3059\u3002\u3057\u304b\u3057\u3001\u3053\u306e\u3088\u3046\u306a\u30d7\u30ed\u30bb\u30b9\u306f\u3001\u65b0\u85ac\u3084\u65e2\u5b58\u306e\u533b\u85ac\u54c1\u3092\u65b0\u3057\u3044\u9069\u5fdc\u75c7\u306e\u305f\u3081\u306b\u4f7f\u7528\u3059\u308b\u969b\u306b\u3001\u4e00\u822c\u306e\u4eba\u3005\u306b\u5408\u7406\u7684\u306b\u5b8c\u5168\u306a\u30d7\u30ed\u30d5\u30a1\u30a4\u30eb\u3092\u63d0\u4f9b\u3059\u308b\u305f\u3081\u306b\u5fc5\u8981\u3067\u3059\u3002\u307e\u305f\u3001\u81e8\u5e8a\u8a66\u9a13\u306e\u53b3\u683c\u3055\u306f\u3001\u65e5\u672c\u3067\u767a\u751f\u3057\u305f\u4e8b\u6545\u306e\u3088\u3046\u306a\u60b2\u5287\u3092\u6700\u5c0f\u9650\u306b\u6291\u3048\u308b\u305f\u3081\u306b\u3082\u5fc5\u8981\u3067\u3059\u3002 <\/span>BIA 10-2474\u88c1\u5224 [9, 10]\u3067\u306f <\/span>Theralizumab\u8a66\u9a13[11]\u3092\u5b9f\u65bd\u3057\u307e\u3057\u305f\u3002 <\/span>\u30aa\u30eb\u30cb\u30c1\u30f3\u30c8\u30e9\u30f3\u30b9\u30ab\u30eb\u30d0\u30df\u30e9\u30fc\u30bc\uff08OTC\uff09\u6b20\u640d\u75c7\u306e\u907a\u4f1d\u5b50\u6cbb\u7642\u8a66\u9a13\u306b\u53c2\u52a0\u3057\u307e\u3057\u305f[12]\u3002 <\/span>\u3084\u30011950\u5e74\u4ee3\u304b\u308960\u5e74\u4ee3\u306b\u304b\u3051\u3066\u306e\u30b5\u30ea\u30c9\u30de\u30a4\u30c9\u4e8b\u4ef6\u306a\u3069\u304c\u3042\u308a\u307e\u3057\u305f[13]\u3002\u00a0<\/span><\/p>\n

\u305d\u308c\u305e\u308c\u306e\u60b2\u5287\u3092\u53d7\u3051\u3066\uff0c\u79d1\u5b66\u754c\uff0c\u533b\u7642\u6a5f\u95a2\uff0c\u653f\u5e9c\u6a5f\u95a2\u306f\uff0c\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u3084\u76f8\u8ac7\u3092\u5897\u3084\u3057\uff0c\u554f\u984c\u3092\u65e9\u671f\u306b\u8a8d\u8b58\u3057\u3066\u88ab\u5bb3\u3092\u9632\u304e\uff0c\u5c06\u6765\u306e\u81e8\u5e8a\u8a66\u9a13\u306e\u9069\u7528\u6027\u3092\u3088\u308a\u9069\u5207\u306b\u8a55\u4fa1\u3059\u308b\u305f\u3081\u306b\uff0c\u591a\u304f\u306e\u53d6\u308a\u7d44\u307f\u3092\u884c\u3063\u3066\u304d\u305f[14-17]\uff0e\u3057\u304b\u3057\uff0c\u5275\u85ac\u304b\u3089\u5e02\u5834\u307e\u3067\u306e\u30d7\u30ed\u30bb\u30b9\u306f\uff0c\u307e\u3060\u5b8c\u74a7\u3068\u306f\u8a00\u3048\u307e\u305b\u3093\uff0e\u3053\u306e\u6570\u30f6\u6708\u306e\u9593\u306b\u3001\u4e16\u754c\u306f\u3001\u79d1\u5b66\u7684\u7814\u7a76\u306b\u304a\u3051\u308b\u8907\u96d1\u3055\u3068\u3001\u3057\u3070\u3057\u3070\u7d50\u8ad6\u304c\u51fa\u306a\u3044\u3053\u3068\u3092\u76ee\u306e\u5f53\u305f\u308a\u306b\u3057\u307e\u3057\u305f\u3002\u6700\u8fd1\u3001\u91cd\u75c7\u306eCOVID-19\u60a3\u8005\u3092\u5bfe\u8c61\u3068\u3057\u305fRemdesivir\u8a66\u9a13\u3067\u826f\u597d\u306a\u7d50\u679c\u304c\u5f97\u3089\u308c\u3001FDA\u306b\u3088\u308b\u627f\u8a8d\u304c\u65e9\u307e\u3063\u305f\u3068\u3044\u3046\u30cb\u30e5\u30fc\u30b9\u304c\u3042\u308a\u307e\u3057\u305f\u304c[18, 19]\u3001\u79c1\u305f\u3061\u306f\u3001\u307e\u3060\u307e\u3060\u3084\u308b\u3079\u304d\u3053\u3068\u304c\u3042\u308b\u3068\u3044\u3046\u3053\u3068\u3092\u518d\u8a8d\u8b58\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u00a0<\/span><\/p>\n

    \n
  1. Ioannidis, J.P.\u3002 <\/span>Why Most Clinical \u30ea\u30b5\u30fc\u30c1<\/a> Is Not Useful.<\/span><\/i> PLoS Med, 2016.13(6): p.e1002049\u3067\u3059\u3002<\/span><\/li>\n
  2. Treweek, S. and M. Zwarenstein, <\/span>\u30c8\u30e9\u30a4\u30a2\u30eb\u3092\u554f\u984c\u306b\u3059\u308b\uff1a\u5b9f\u7528\u7684\u30c8\u30e9\u30a4\u30a2\u30eb\u3001\u8aac\u660e\u7684\u30c8\u30e9\u30a4\u30a2\u30eb\u3068\u9069\u7528\u6027\u306e\u554f\u984c\u3002<\/span><\/i> \u30c8\u30e9\u30a4\u30a2\u30eb, 2009.10: p. 37.<\/span><\/li>\n
  3. Slattery, P., A.K. Saeri, and P. Bragge, <\/span>\u5065\u5eb7\u306b\u304a\u3051\u308b\u7814\u7a76\u306e\u5171\u540c\u30c7\u30b6\u30a4\u30f3\uff1a\u30ec\u30d3\u30e5\u30fc\u306e\u8fc5\u901f\u306a\u6982\u89b3\u3002<\/span><\/i> Health Res Policy Syst, 2020.18(1): p. 17.<\/span><\/li>\n
  4. \u30ec\u30a4\u30ce\u30eb\u30ba\u3001T\uff0e <\/span>\u81e8\u5e8a\u8a66\u9a13\uff1a\u53c2\u52a0\u8005\u304c\u5c11\u306a\u3044\u3068\u3044\u3046\u554f\u984c\u306f\u30c6\u30af\u30ce\u30ed\u30b8\u30fc\u3067\u89e3\u6c7a\u3067\u304d\u308b\u306e\u304b\uff1f<\/span><\/i> BMJ, 2011.342: p. d3662.<\/span><\/li>\n
  5. Lehmann, B.A., et al, <\/span>\"And Then He Got into the Wrong Group\":\u7121\u4f5c\u70ba\u5316\u5bfe\u7167\u8a66\u9a13\u306e\u52df\u96c6\u306b\u304a\u3051\u308b\u7121\u4f5c\u70ba\u5316\u306e\u52b9\u679c\u3092\u63a2\u308b\u8cea\u7684\u7814\u7a76\u3002<\/span><\/i> Int J Environ Res Public Health, 2020.17(6).<\/span><\/li>\n
  6. Cleland , J.G.F., et al, <\/span>\u81e8\u5e8a\u8a66\u9a13\u306b\u304a\u3051\u308b\u30d5\u30a9\u30ed\u30fc\u30a2\u30c3\u30d7\u306e\u640d\u5931\u3092\u6e1b\u3089\u3059\u65b9\u6cd5\uff1a\u30a4\u30f3\u30d5\u30a9\u30fc\u30e0\u30c9\u30b3\u30f3\u30bb\u30f3\u30c8\u3001\u540c\u610f\u306e\u64a4\u56de<\/span><\/i> \u30e8\u30fc\u30ed\u30d4\u30a2\u30f3\u30fb\u30b8\u30e3\u30fc\u30ca\u30eb\u30fb\u30aa\u30d6\u30fb\u30cf\u30fc\u30c8\u30fb\u30d5\u30a7\u30a4\u30eb\u30ba 20046<\/span><\/li>\n<\/ol>\n

    \u00a0<\/b>(1).<\/span><\/p>\n

      \n
    1. \u5bae\u5ddd\u54f2\u4e5f\u3055\u3093\u3002 <\/span>\u751f\u30c7\u30fc\u30bf\u304c\u306a\u3051\u308c\u3070\u79d1\u5b66\u3082\u3067\u304d\u306a\u3044\uff1a\u518d\u73fe\u6027\u306e\u5371\u6a5f\u306e\u3082\u3046\u4e00\u3064\u306e\u539f\u56e0\u3068\u8003\u3048\u3089\u308c\u307e\u3059\u3002<\/span><\/i> Mol Brain, 2020. <\/span>13<\/b>(1): p. 24.<\/span><\/li>\n
    2. Raj, N., et al, <\/span>\u5e02\u8ca9\u5f8c\u8abf\u67fb\uff1a\u30a4\u30ae\u30ea\u30b9\u3068\u30ab\u30ca\u30c0\u306e\u4e8b\u4f8b\u3092\u3082\u3068\u306b\u3001\u52b9\u679c\u7684\u306b\u6a5f\u80fd\u3059\u308b\u305f\u3081\u306e\u91cd\u8981\u306a\u5074\u9762\u3068\u5bfe\u7b56\u3092\u30ec\u30d3\u30e5\u30fc\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/i> Ther Adv Drug Saf, 2019. <\/span>10<\/b>: p. 2042098619865413.<\/span><\/li>\n
    3. \u30e9\u30f3\u30c0\u30fc\u30bd\u30f3\u3001J\uff0e <\/span>\u81f4\u547d\u7684\u306a\u30d5\u30e9\u30f3\u30b9\u306e\u81e8\u5e8a\u8a66\u9a13\u3067\u306f\u3001\u85ac\u306e\u6295\u4e0e\u91cf\u3092\u5897\u3084\u3059\u524d\u306b\u30c7\u30fc\u30bf\u3092\u78ba\u8a8d\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u305b\u3093\u3067\u3057\u305f\u3002<\/span><\/i> Nature News, 2016\u300d\u306b\u63b2\u8f09\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/span><\/li>\n
    4. Kaur, R., P. Sidhu, and S. Singh, <\/span>BIA 10-2474\u306e\u7b2cI\u76f8\u81e8\u5e8a\u8a66\u9a13\u306e\u5931\u6557\u306f\uff1f\u30b0\u30ed\u30fc\u30d0\u30eb\u306a\u601d\u60d1\u3068\u4eca\u5f8c\u306e\u30d5\u30a7\u30fc\u30baI\u8a66\u9a13\u3078\u306e\u63d0\u8a00\u3002<\/span><\/i> J Pharmacol Pharmacother, 2016. <\/span>7<\/b>(3): p. 120-6.<\/span><\/li>\n
    5. \u30a2\u30bf\u30eb\u30ef\u30e9\u3001H\uff0e <\/span>TGN1412\uff1a\u767a\u898b\u304b\u3089\u707d\u5bb3\u307e\u3067\u3002<\/span><\/i> J Young Pharm, 2010. <\/span>2<\/b>(3): p. 332-6.<\/span><\/li>\n
    6. Rinde, M.., <\/span>\u30b8\u30a7\u30b7\u30fc\u30fb\u30b2\u30eb\u30b7\u30f3\u30ac\u30fc\u306e\u6b7b\u300120\u5e74\u5f8c\u306b<\/span><\/i>\u3067\u3042\u308b\u3002 <\/span>\u79d1\u5b66\u53f2\u7814\u7a76\u6240 - \u84b8\u7559<\/span><\/i>. 2019.<\/span><\/li>\n
    7. \u30f4\u30a1\u30eb\u30b2\u30c3\u30bd\u30f3\u3001N, <\/span>\u30b5\u30ea\u30c9\u30de\u30a4\u30c9\u306b\u3088\u308b\u50ac\u5947\u5f62\u6027\uff1a\u6b74\u53f2\u3068\u30e1\u30ab\u30cb\u30ba\u30e0\u3002<\/span><\/i> Birth Defects Res C Embryo Today, 2015. <\/span>105<\/b>(2): p. 140-56.<\/span><\/li>\n
    8. Lipman, P.D., L.Dluzak, and C.M.Stoney, <\/span>\u3053\u306e\u7814\u7a76\u306f\u5b9f\u73fe\u53ef\u80fd\u304b\uff1f\u6bb5\u968e\u7684\u306a\u52a9\u6210\u30e1\u30ab\u30cb\u30ba\u30e0\u306e\u4e0b\u3067\u3001\u30d7\u30e9\u30b0\u30de\u30c6\u30a3\u30c3\u30af\u306a\u8a66\u9a13\u8a08\u753b\u306e\u30de\u30a4\u30eb\u30b9\u30c8\u30fc\u30f3\u306e\u7ba1\u7406\u3092\u5bb9\u6613\u306b\u3059\u308b\u3002<\/span><\/i> \u30c8\u30e9\u30a4\u30a2\u30eb\u30012019\u5e74\u3002 <\/span>20<\/b>(1): p. 307.<\/span><\/li>\n
    9. Dal-R\u00e9, R., P. Janiaud, and J.P.A. Ioannidis, <\/span>\u30ea\u30a2\u30eb\u30ef\u30fc\u30eb\u30c9\u306e\u30a8\u30d3\u30c7\u30f3\u30b9\u3002\u5b9f\u8df5\u7684\u3068\u8868\u793a\u3055\u308c\u305f\u7121\u4f5c\u70ba\u5316\u6bd4\u8f03\u8a66\u9a13\u306f\u3069\u306e\u7a0b\u5ea6\u5b9f\u8df5\u7684\u306a\u306e\u304b\uff1f<\/span><\/i> BMC Med, 2018\u300d\u3067\u3059\u3002 <\/span>16<\/b>(1): p. 49.<\/span><\/li>\n
    10. Reijers, J.A.A., et al, <\/span>\u4e0d\u7d14\u7269\u306b\u3088\u308b\u514d\u75ab\u8ce6\u6d3b\u5316\u306e\u5f0a\u5bb3\u3002\u30d0\u30a4\u30aa\u533b\u85ac\u54c1\u306e\u30c0\u30fc\u30af\u30b5\u30a4\u30c9<\/span><\/i> Br J Clin Pharmacol, 2019. <\/span>85<\/b>(7): p. 1418-1426.<\/span><\/li>\n
    11. \u30f4\u30a1\u30f3\u30fb\u30ce\u30fc\u30de\u30f3\u3001G.A.\u3002 <\/span>\u81e8\u5e8a\u8a66\u9a13\u306b\u304a\u3051\u308b\u6bd2\u6027\u3092\u4e88\u6e2c\u3059\u308b\u305f\u3081\u306e\u52d5\u7269\u5b9f\u9a13\u306e\u9650\u754c\u3002\u73fe\u5728\u306e\u30a2\u30d7\u30ed\u30fc\u30c1\u3092\u518d\u8003\u3059\u308b\u6642\u304c\u6765\u305f\u306e\u304b\uff1f<\/span><\/i> JACC Basic Transl Sci, 2019. <\/span>4<\/b>(7): p. 845-854.<\/span><\/li>\n
    12. \u75be\u60a3\u3001N.I.o.A.I, <\/span>NIH\u306e\u81e8\u5e8a\u8a66\u9a13\u3067\u30ec\u30e0\u30c7\u30b7\u30d3\u30eb\u304c\u9032\u884c\u6027COVID-19\u304b\u3089\u306e\u56de\u5fa9\u3092\u4fc3\u9032\u3059\u308b\u3053\u3068\u304c\u5224\u660e<\/span><\/i>, N.I.o. Health, Editor.2020.<\/span><\/li>\n
    13. Gilead\u3002 <\/span>Gilead\u793e\u3001\u91cd\u75c7COVID-19\u60a3\u8005\u3092\u5bfe\u8c61\u3068\u3057\u305f\u6297\u30a6\u30a4\u30eb\u30b9\u5264Remdesivir\u306e\u7b2c3\u76f8\u8a66\u9a13\u306e\u7d50\u679c\u3092\u767a\u8868<\/span><\/i>, \u30ae\u30ea\u30a2\u30c9\u793e, \u7de8\u96c6\u90e82020.<\/span><\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"

      Scientific studies are designed with a number of control experiments and replications such that the answer to the question being investigated is clear. In complex experimental set-ups like clinical trials, results are often less clear making extrapolation of data impossible [1]. In fact, reports have indicated that many clinical trials are insufficiently designed, yielding ambiguous or useless results [1-3]. Other issues such as recruiting enough patients for the correct sampling size [4], bias and perceptions during recruitment [2, 5], patient withdrawal from a trial [5, 6], non-transparency or lack of enough expert review [1, 7] are very real factors that may confound the study making clear cut conclusions hard to<\/p>\n

      \u7d9a\u304d\u3092\u8aad\u3080<\/a><\/div>","protected":false},"author":12,"featured_media":7750,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[435],"tags":[],"acf":[],"yoast_head":"\nThe Difficulties in Clinical Trials - The Kolabtree Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kolabtree.com\/blog\/ja\/the-difficulties-in-clinical-trials\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Difficulties in Clinical Trials\" \/>\n<meta property=\"og:description\" content=\"Scientific studies are designed with a number of control experiments and replications such that the answer to the question being investigated is clear. In complex experimental set-ups like clinical trials, results are often less clear making extrapolation of data impossible [1]. In fact, reports have indicated that many clinical trials are insufficiently designed, yielding ambiguous or useless results [1-3]. Other issues such as recruiting enough patients for the correct sampling size [4], bias and perceptions during recruitment [2, 5], patient withdrawal from a trial [5, 6], non-transparency or lack of enough expert review [1, 7] are very real factors that may confound the study making clear cut conclusions hard toRead More\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.kolabtree.com\/blog\/ja\/the-difficulties-in-clinical-trials\/\" \/>\n<meta property=\"og:site_name\" content=\"The Kolabtree Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/kolabtree\" \/>\n<meta property=\"article:published_time\" content=\"2020-06-05T11:44:07+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2020-06-05T11:55:08+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2020\/06\/The-Difficulties-in-Clinical-Trials.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1280\" \/>\n\t<meta property=\"og:image:height\" content=\"877\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Ramya Sriram\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@kolabtree\" \/>\n<meta name=\"twitter:site\" content=\"@kolabtree\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ramya Sriram\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593\" \/>\n\t<meta name=\"twitter:data2\" content=\"4\u5206\" \/>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"The Difficulties in Clinical Trials - The Kolabtree Blog","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.kolabtree.com\/blog\/ja\/the-difficulties-in-clinical-trials\/","og_locale":"ja_JP","og_type":"article","og_title":"The Difficulties in Clinical Trials","og_description":"Scientific studies are designed with a number of control experiments and replications such that the answer to the question being investigated is clear. In complex experimental set-ups like clinical trials, results are often less clear making extrapolation of data impossible [1]. In fact, reports have indicated that many clinical trials are insufficiently designed, yielding ambiguous or useless results [1-3]. Other issues such as recruiting enough patients for the correct sampling size [4], bias and perceptions during recruitment [2, 5], patient withdrawal from a trial [5, 6], non-transparency or lack of enough expert review [1, 7] are very real factors that may confound the study making clear cut conclusions hard toRead More","og_url":"https:\/\/www.kolabtree.com\/blog\/ja\/the-difficulties-in-clinical-trials\/","og_site_name":"The Kolabtree Blog","article_publisher":"https:\/\/www.facebook.com\/kolabtree","article_published_time":"2020-06-05T11:44:07+00:00","article_modified_time":"2020-06-05T11:55:08+00:00","og_image":[{"width":1280,"height":877,"url":"https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2020\/06\/The-Difficulties-in-Clinical-Trials.jpg","type":"image\/jpeg"}],"author":"Ramya Sriram","twitter_card":"summary_large_image","twitter_creator":"@kolabtree","twitter_site":"@kolabtree","twitter_misc":{"\u57f7\u7b46\u8005":"Ramya Sriram","\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593":"4\u5206"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/#article","isPartOf":{"@id":"https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/"},"author":{"name":"Ramya Sriram","@id":"https:\/\/www.kolabtree.com\/blog\/#\/schema\/person\/81992f5863a1b06d132a47822e7b4400"},"headline":"The Difficulties in Clinical Trials","datePublished":"2020-06-05T11:44:07+00:00","dateModified":"2020-06-05T11:55:08+00:00","mainEntityOfPage":{"@id":"https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/"},"wordCount":741,"commentCount":0,"publisher":{"@id":"https:\/\/www.kolabtree.com\/blog\/#organization"},"articleSection":["Research"],"inLanguage":"ja","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/","url":"https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/","name":"The Difficulties in Clinical Trials - The Kolabtree Blog","isPartOf":{"@id":"https:\/\/www.kolabtree.com\/blog\/#website"},"datePublished":"2020-06-05T11:44:07+00:00","dateModified":"2020-06-05T11:55:08+00:00","breadcrumb":{"@id":"https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/#breadcrumb"},"inLanguage":"ja","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.kolabtree.com\/blog\/pt\/the-difficulties-in-clinical-trials\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.kolabtree.com\/blog\/"},{"@type":"ListItem","position":2,"name":"The Difficulties in Clinical Trials"}]},{"@type":"WebSite","@id":"https:\/\/www.kolabtree.com\/blog\/#website","url":"https:\/\/www.kolabtree.com\/blog\/","name":"The Kolabtree Blog","description":"Expert Views on Science, Innovation and Product Development","publisher":{"@id":"https:\/\/www.kolabtree.com\/blog\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.kolabtree.com\/blog\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"ja"},{"@type":"Organization","@id":"https:\/\/www.kolabtree.com\/blog\/#organization","name":"Kolabtree","url":"https:\/\/www.kolabtree.com\/blog\/","logo":{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/www.kolabtree.com\/blog\/#\/schema\/logo\/image\/","url":"","contentUrl":"","caption":"Kolabtree"},"image":{"@id":"https:\/\/www.kolabtree.com\/blog\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/kolabtree","https:\/\/twitter.com\/kolabtree","https:\/\/instagram.com\/kolabtree","https:\/\/www.linkedin.com\/company\/kolabtree","https:\/\/en.m.wikipedia.org\/wiki\/Kolabtree"]},{"@type":"Person","@id":"https:\/\/www.kolabtree.com\/blog\/#\/schema\/person\/81992f5863a1b06d132a47822e7b4400","name":"Ramya Sriram","image":{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/www.kolabtree.com\/blog\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/8100b45c960ebbbbe420e8b3f250515f?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/8100b45c960ebbbbe420e8b3f250515f?s=96&d=mm&r=g","caption":"Ramya Sriram"},"description":"Ramya Sriram manages digital content and communications at Kolabtree (kolabtree.com), the world's largest freelancing platform for scientists. 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