<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02195076</url>
  </required_header>
  <id_info>
    <org_study_id>0695-13-SMC</org_study_id>
    <nct_id>NCT02195076</nct_id>
  </id_info>
  <brief_title>Non Invasive Detection of Lung and Breast Cancer by Odor Signature</brief_title>
  <official_title>A Clinical Study Design to Evaluate the Specificity and Sensitivity of Our Novel System for Detection of Breast and Lung Cancer by Odor Signature</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>BioSense Medical LTD</agency>
      <agency_class>Industry</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Sheba Medical Center</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>BioSense Medical LTD</source>
  <brief_summary>
    <textblock>
      The investigators have developed an early detection solution for lung and breast cancer. A&#xD;
      system which can distinguish between different medical odors based on biosensors. Our product&#xD;
      is user-friendly noninvasive, nonradioactive and nontoxic to the patients. The technology&#xD;
      enables a high level of sensitivity and provides users with a quick lab response and a simple&#xD;
      yes or no answer.&#xD;
&#xD;
      The aim of this study is to contribute and detect the patient at the earliest possible stage,&#xD;
      in a noninvasive, nonradioactive and nontoxic way. Exhaled breath and urine samples are a&#xD;
      promising approach towards future possible lung and breast cancer screening method.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Early detection of cancer can dramatically improve the survival chances. to date, there is no&#xD;
      efficient diagnostic tool for detection of lung cancer in early stages. Regarding breast&#xD;
      cancer, the common screening tool us mammography, which suffer from low sensitivity and high&#xD;
      false positive. Thus, there is an urgent need for developing a screening tool for early&#xD;
      stages lung and breast cancer.&#xD;
&#xD;
      The sense of smell depends on the ability of specialized sensory cells of the nose to&#xD;
      perceive volatile compounds (VOCs). Diseases such as infections and malignancies can be&#xD;
      associated with changes in host metabolism, accompanied by production of different VOCs, and&#xD;
      thus a different odor. Several studies have shown that different cancers secrete different&#xD;
      VOCs, thus produce different smell.&#xD;
&#xD;
      We have developed a system which uses biosensors that can scent the VOCs that lung and breast&#xD;
      cancer cell produce, thus distinguish between healthy control and lung or breast cancer.&#xD;
      These biosensors can detect low stages lung and breast cancer.&#xD;
&#xD;
      Patients will supply urine samples and exhaled breath samples using a kit that we will&#xD;
      supply. The samples will be shipped to our lab, where they will be processed and the VOCs&#xD;
      will be separated from the head space of the samples. The biosensors will be exposed to the&#xD;
      VOCs samples and will report whether the specific sample id cancerous (lung or breast) or&#xD;
      not.&#xD;
&#xD;
      The Data will be collected from all samples and statistical analysis will be calculated, in&#xD;
      order to test the specificity and sensitivity of our biosensors to detect cancerous samples.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date>July 2014</start_date>
  <primary_completion_date type="Anticipated">July 2017</primary_completion_date>
  <study_type>Observational [Patient Registry]</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Control</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <target_duration>3 Years</target_duration>
  <primary_outcome>
    <measure>The sensitivity and specificity of our biosensors in lung and breast cancer detection</measure>
    <time_frame>3 years</time_frame>
    <description>We will measure the ability of our biosensors to detect lung and breast cancer in urine samples from patients. Each urine sample will be subjected to 5 biosensors. If 3 out of 5 will report positively, the sample will be marked as cancerous. Each type of cancer (lung or breast) will be detected by different groups of biosensors, trained specifically to detect the specific cancer type.&#xD;
After the data of the detections will be collected, statistical analysis will be calculated in order to evaluate the sensitivity and specificity of our biosensor in cancer detection.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Testing the ability of our biosensors to distinguish between different sub- types of breast and lung cancer.</measure>
    <time_frame>3 years</time_frame>
    <description>After the collection of the detection data (primary outcome measure), we will compare it to the patients data records (in terms of staging, CT, pathology, biological markers etc.) and evaluate whether our biosensors can detect different sub- types of lung and breast cancer in different sensitivity and specifity.</description>
  </secondary_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Anticipated">400</enrollment>
  <condition>Lung Cancer</condition>
  <condition>Breast Cancer</condition>
  <arm_group>
    <arm_group_label>Breast Cancer patients</arm_group_label>
  </arm_group>
  <arm_group>
    <arm_group_label>Lung cancer patients</arm_group_label>
  </arm_group>
  <arm_group>
    <arm_group_label>Healthy controls</arm_group_label>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>non-invasive detection of cancer odor</intervention_name>
    <description>The odor VOCs of the specimens will be subjected to our system for detection by the biosensors. If the sample is cancerous the biosensors will report it (YES signal). If the sample s not cancerous, the biosensors will not report it (NO signal).</description>
    <arm_group_label>Breast Cancer patients</arm_group_label>
    <arm_group_label>Healthy controls</arm_group_label>
    <arm_group_label>Lung cancer patients</arm_group_label>
  </intervention>
  <biospec_retention>Samples Without DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      urine samples and exhaled breath samples&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Breast Cancer patient after diagnosis. Lung Cancer patients after diagnosis. Healthy&#xD;
        controls, matching gender and age.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Diagnosed Lung Cancer patients&#xD;
&#xD;
          -  Diagnosed Breast Cancer patients&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Cancer patients who were treated using chemotherapy&#xD;
&#xD;
          -  Cancer patients who were treated using radiation&#xD;
&#xD;
          -  Cancer patients who were treated using biological treatments&#xD;
&#xD;
          -  Cancer patients who were treated with chemotherapy&#xD;
&#xD;
          -  Cancer patients who were treated with any anti- cancer therapies&#xD;
&#xD;
          -  Cancer patients who use drugs that affect the immune system&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>30 Years</minimum_age>
    <maximum_age>80 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Michal Mark Danieli, PhD</last_name>
    <phone>+972-4-7706816</phone>
    <email>Michal@biosensem.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Asher Castiel, PhD</last_name>
    <phone>+972-4-7706816</phone>
    <email>asher.castiel@biosensem.com</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Sheba Medical Center</name>
      <address>
        <city>Tel Hashomer, Ramat- Gan</city>
        <zip>52621</zip>
        <country>Israel</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Einav Gal-Yam, MD PhD</last_name>
      <email>Einav.NiliGal-Yam@sheba.health.gov.il</email>
    </contact>
    <contact_backup>
      <last_name>Yair Bar, MD</last_name>
      <email>Yair.bar@sheba.health.gov.il</email>
    </contact_backup>
    <investigator>
      <last_name>Einav Gal- Yam, M.D Ph.D</last_name>
      <role>Principal Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>Israel</country>
  </location_countries>
  <verification_date>July 2014</verification_date>
  <study_first_submitted>July 16, 2014</study_first_submitted>
  <study_first_submitted_qc>July 17, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">July 21, 2014</study_first_posted>
  <last_update_submitted>July 17, 2014</last_update_submitted>
  <last_update_submitted_qc>July 17, 2014</last_update_submitted_qc>
  <last_update_posted type="Estimate">July 21, 2014</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Lung cancer</keyword>
  <keyword>Breast Cancer</keyword>
  <keyword>Biosensors</keyword>
  <keyword>Volatile Organic Compounds</keyword>
  <keyword>Odor</keyword>
  <keyword>Urine Sample</keyword>
  <keyword>Exhaled Breath Samples</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Breast Neoplasms</mesh_term>
    <mesh_term>Lung Neoplasms</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02195076
org study id: 0695-13-SMC
nct id: NCT02195076
lead sponsor: 
collaborator: 
The investigators have developed an early detection solution for lung and breast cancer. A
      system which can distinguish between different medical odors based on biosensors. Our product
      is user-friendly noninvasive, nonradioactive and nontoxic to the patients. The technology
      enables a high level of sensitivity and provides users with a quick lab response and a simple
      yes or no answer.

      The aim of this study is to contribute and detect the patient at the earliest possible stage,
      in a noninvasive, nonradioactive and nontoxic way. Exhaled breath and urine samples are a
      promising approach towards future possible lung and breast cancer screening method.
Early detection of cancer can dramatically improve the survival chances. to date, there is no
      efficient diagnostic tool for detection of lung cancer in early stages. Regarding breast
      cancer, the common screening tool us mammography, which suffer from low sensitivity and high
      false positive. Thus, there is an urgent need for developing a screening tool for early
      stages lung and breast cancer.

      The sense of smell depends on the ability of specialized sensory cells of the nose to
      perceive volatile compounds (VOCs). Diseases such as infections and malignancies can be
      associated with changes in host metabolism, accompanied by production of different VOCs, and
      thus a different odor. Several studies have shown that different cancers secrete different
      VOCs, thus produce different smell.

      We have developed a system which uses biosensors that can scent the VOCs that lung and breast
      cancer cell produce, thus distinguish between healthy control and lung or breast cancer.
      These biosensors can detect low stages lung and breast cancer.

      Patients will supply urine samples and exhaled breath samples using a kit that we will
      supply. The samples will be shipped to our lab, where they will be processed and the VOCs
      will be separated from the head space of the samples. The biosensors will be exposed to the
      VOCs samples and will report whether the specific sample id cancerous (lung or breast) or
      not.

      The Data will be collected from all samples and statistical analysis will be calculated, in
      order to test the specificity and sensitivity of our biosensors to detect cancerous samples.
observational model: Case-Control
time perspective: Prospective
measure: The sensitivity and specificity of our biosensors in lung and breast cancer detection
time frame: 3 years
description: We will measure the ability of our biosensors to detect lung and breast cancer in urine samples from patients. Each urine sample will be subjected to 5 biosensors. If 3 out of 5 will report positively, the sample will be marked as cancerous. Each type of cancer (lung or breast) will be detected by different groups of biosensors, trained specifically to detect the specific cancer type.
After the data of the detections will be collected, statistical analysis will be calculated in order to evaluate the sensitivity and specificity of our biosensor in cancer detection.
measure: Testing the ability of our biosensors to distinguish between different sub- types of breast and lung cancer.
time frame: 3 years
description: After the collection of the detection data (primary outcome measure), we will compare it to the patients data records (in terms of staging, CT, pathology, biological markers etc.) and evaluate whether our biosensors can detect different sub- types of lung and breast cancer in different sensitivity and specifity.
arm group label: Breast Cancer patients
arm group label: Lung cancer patients
arm group label: Healthy controls
intervention type: Other
intervention name: non-invasive detection of cancer odor
description: The odor VOCs of the specimens will be subjected to our system for detection by the biosensors. If the sample is cancerous the biosensors will report it (YES signal). If the sample s not cancerous, the biosensors will not report it (NO signal).
arm group label: Breast Cancer patients
arm group label: Healthy controls
arm group label: Lung cancer patients
urine samples and exhaled breath samples
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 30 Years
maximum age: 80 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Michal Mark Danieli, PhD
phone: +972-4-7706816
email: Michal@biosensem.com
last name: Asher Castiel, PhD
phone: +972-4-7706816
email: asher.castiel@biosensem.com
facility: 
status: Recruiting
contact: 
contact backup: 
investigator: 
country: Israel
responsible party type: Sponsor
mesh term: Breast Neoplasms
mesh term: Lung Neoplasms