ehrlink/rxnorm-ingredient-map.ipynb

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   "source": [
    "import requests\n",
    "import xml.etree.ElementTree\n",
    "import time\n",
    "import os\n",
    "import csv\n",
    "\n",
    "import pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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   "source": [
    "def get_rxnorm_ingredients(rxcui):\n",
    "    \"\"\"\n",
    "    Return a generator of RxNorm ingredients related to the provided RxNorm concept.\n",
    "    Each ingredient is a (rxcui, name, umlscui) tuple. This function calls the\n",
    "    RxNormAPI as documented here:\n",
    "    http://rxnav.nlm.nih.gov/RxNormAPIs.html#uLink=RxNorm_REST_getAllRelatedInfo\n",
    "    \"\"\"\n",
    "    base_uri = 'http://rxnav.nlm.nih.gov/REST'\n",
    "    url = '{base_uri}/rxcui/{rxcui}/allrelated'.format(base_uri = base_uri, rxcui = rxcui)\n",
    "    response = requests.get(url)\n",
    "    tree = xml.etree.ElementTree.fromstring(response.text)\n",
    "    xml_ingredients = tree.findall(\"./allRelatedGroup/conceptGroup[tty='IN']/conceptProperties\")\n",
    "    for xml_ingredient in xml_ingredients:\n",
    "        assert xml_ingredient.findtext('tty') == 'IN'\n",
    "        yield tuple(xml_ingredient.findtext(tag) for tag in ['rxcui', 'name', 'umlscui'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>medication</th>\n",
       "      <th>medication_definition_id</th>\n",
       "      <th>indications</th>\n",
       "      <th>rxcui</th>\n",
       "      <th>score</th>\n",
       "      <th>rank</th>\n",
       "      <th>nAtoms</th>\n",
       "      <th>name</th>\n",
       "      <th>synonym</th>\n",
       "      <th>tty</th>\n",
       "      <th>language</th>\n",
       "      <th>suppress</th>\n",
       "      <th>umlscui</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4-Aminopyridine Powder</td>\n",
       "      <td>108483</td>\n",
       "      <td>1</td>\n",
       "      <td>897018</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "      <td>12</td>\n",
       "      <td>dalfampridine</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IN</td>\n",
       "      <td>ENG</td>\n",
       "      <td>N</td>\n",
       "      <td>C0000477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Abilify 1 MG/ML Oral Solution</td>\n",
       "      <td>123191</td>\n",
       "      <td>2</td>\n",
       "      <td>544412</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>aripiprazole 1 MG/ML Oral Solution [Abilify]</td>\n",
       "      <td>Abilify 1 MG/ML Oral Solution</td>\n",
       "      <td>SBD</td>\n",
       "      <td>ENG</td>\n",
       "      <td>N</td>\n",
       "      <td>C1586223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Abilify 10 MG Oral Tablet</td>\n",
       "      <td>104197</td>\n",
       "      <td>11</td>\n",
       "      <td>352307</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>aripiprazole 10 MG Oral Tablet [Abilify]</td>\n",
       "      <td>Abilify 10 MG Oral Tablet</td>\n",
       "      <td>SBD</td>\n",
       "      <td>ENG</td>\n",
       "      <td>N</td>\n",
       "      <td>C1169930</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      medication  medication_definition_id  indications  \\\n",
       "1         4-Aminopyridine Powder                    108483            1   \n",
       "2  Abilify 1 MG/ML Oral Solution                    123191            2   \n",
       "3      Abilify 10 MG Oral Tablet                    104197           11   \n",
       "\n",
       "    rxcui  score  rank  nAtoms                                          name  \\\n",
       "1  897018     67     5      12                                 dalfampridine   \n",
       "2  544412    100     1       7  aripiprazole 1 MG/ML Oral Solution [Abilify]   \n",
       "3  352307    100     1      16      aripiprazole 10 MG Oral Tablet [Abilify]   \n",
       "\n",
       "                         synonym  tty language suppress   umlscui  \n",
       "1                            NaN   IN      ENG        N  C0000477  \n",
       "2  Abilify 1 MG/ML Oral Solution  SBD      ENG        N  C1586223  \n",
       "3      Abilify 10 MG Oral Tablet  SBD      ENG        N  C1169930  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the rxnorm mappings to ehrlink medications computed by antoine lizee\n",
    "url = 'https://raw.githubusercontent.com/antoine-lizee/RRxNorm/master/Output/allMatchesWithProperties.csv'\n",
    "med_df = pandas.read_csv(url, index_col=0)\n",
    "med_df[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No ingredients found for 1151137 DFG Oral Liquid Product\n",
      "No ingredients found for 7067 DF Mouthwash\n"
     ]
    }
   ],
   "source": [
    "# Read the rxnorm mappings to ehrlink medications computed by antoine lizee\n",
    "\n",
    "# Prepare the write file\n",
    "path = os.path.join('data', 'rxnorm-as-ingredient.tsv')\n",
    "write_file = open(path, 'w')\n",
    "header = ['input_rxcui', 'input_tty', 'input_name', 'n_ingredients',\n",
    "          'ingredient_rxcui', 'ingredient_name', 'ingredient_umlscui']\n",
    "writer = csv.DictWriter(write_file, delimiter='\\t', fieldnames=header)\n",
    "writer.writeheader()\n",
    "\n",
    "# Query the RxNorm API for each concept.\n",
    "for rxcui, tty, name in set(zip(med_df.rxcui, med_df.tty, med_df.name)):\n",
    "    ingredients = list(get_rxnorm_ingredients(rxcui))\n",
    "    input_dict = {'input_rxcui': rxcui, 'input_tty': tty, 'input_name': name, 'n_ingredients': len(ingredients)}\n",
    "    if not ingredients:\n",
    "        print('No ingredients found for', rxcui, tty, name)\n",
    "    for ingredient in ingredients:\n",
    "        ingr_dict = input_dict.copy()\n",
    "        for tag, value in zip(['ingredient_rxcui', 'ingredient_name', 'ingredient_umlscui'], ingredient):\n",
    "            ingr_dict[tag] = value\n",
    "        writer.writerow(ingr_dict)\n",
    "    time.sleep(2)\n",
    "\n",
    "# Close the completed file\n",
    "write_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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