updates to cou

color3_module/static/COU.md

@@ -52,7 +52,7 @@ The CHRIS - Color additives module provides clinically relevant, yet still conse
 1. The CA is homogeneously distributed throughout the polymer.
 1. The smallest dimension of the colored device component is much greater than the size of any color additive particles that may be present (<= 50x).
 
-While these assumptions are typically valid for color additive containing device components, users of the tool must confirm conformance to the underlying assumptions or provide supporting justification to ensure compliance for a given system.  Further, CHRIS only enables system specific exposure estimates for fifty-three (53) polymeric systems that are generally biostable (non-swelling and non-degrading) and contain less than 2 % m/v of a given CA.  To estimate CA release based on the model, the diffusion coefficient of the CA in the polymer matrix must be specified.  For the fifty-three (53) listed polymeric systems, a worst-case (upper bound) diffusion coefficient, as a function of additive molecular weight, has been established based on data from the literature.  For polymer matrices that are not included in this list, CHRIS assigns an ultra-conservative diffusion coefficient that assumes the polymer has the properties of water.  Note that the worst-case diffusion coefficient is only defined over a molecular weight range of up to 1100 g/mol.  Therefore, for substances with a molecular weight > 1100 g/mol, the value of the diffusion coefficient assuming a molecular weight of 1100 g/mol can be used as a conservative value.
+While these assumptions are typically valid for color additive containing device components, users of the tool must confirm conformance to the underlying assumptions or provide supporting justification to ensure compliance for a given system.  Further, CHRIS only enables system specific exposure estimates for fifty-three (53) polymeric systems that are generally biostable (non-swelling and non-degrading) and contain less than 2 % m/v of a given CA.  To estimate CA release based on the model, the diffusion coefficient of the CA in the polymer matrix must be specified.  For the fifty-three (53) listed polymeric systems, a worst-case (upper bound) diffusion coefficient, as a function of additive molecular weight, has been established based on data from the literature.  For polymer matrices that are not included in this list ("Other polymer"), CHRIS has two approaches.  If the polymer glass transition temperature is not specified, an ultra-conservative diffusion coefficient that assumes the polymer has the properties of water is used.  If the glass transition temperature is specified, a less-conservative upper bound diffusion coefficient is estimated using a machine learning method.  For the listed polymeric systems and the ultra-conservative assumption, note that the worst-case diffusion coefficient is only defined over a molecular weight range of up to 1100 g/mol.  Therefore, for substances with a molecular weight > 1100 g/mol, the value of the diffusion coefficient assuming a molecular weight of 1100 g/mol is used as a conservative value.  When the machine learning method is used, a check is conducted to verify that the polymer/solute combination falls inside the applicability domain of the model.  If it falls outside that domain, CHRIS instead uses the ultra-conservative assumption.  Additionally, polymers with high fractional free volume (FFV) should not be used with the machine learning method because the diffusivity may be underestimated.  Instead, the ultra-conservative assumption should be used.
 
 [^1]: The term "color additive", as defined under section 201(t) of the FD&C Act, means a material which:
  

exposure3_module/static/exposure_COU.md

@@ -29,6 +29,6 @@ CHRIS provides clinically relevant, yet still conservative, exposure dose estima
 1. The total amount of the chemical is present in dilute concentrations (<= 2 m/v %).
 1. Any particles/aggregates of the chemical present in the polymer are much smaller than the smallest component dimension (<= 50x).
 
-While these assumptions are typically valid for bulk additives and impurities in biostable polymers, users of CHRIS must confirm conformance to the underlying assumptions or provide supporting justification to ensure compliance for a given system.  Further, CHRIS only enables system specific exposure estimates for fifty-three (53) polymeric systems that are generally biostable (non-swelling and non-degrading).  To estimate chemical release based on the model, the diffusion coefficient of the chemical in the polymer matrix must be specified.  For the fifty-three (53) listed polymeric systems, a worst-case (upper bound) diffusion coefficient, as a function of molecular weight, has been established based on data from the literature.  For polymer matrices that are not included in this list ("Other polymer"), CHRIS has two approaches.  If the polymer glass transition temperature is not specified, an ultra-conservative diffusion coefficient that assumes the polymer has the properties of water is used.  If the glass transition temperature is specified, a less-conservative upper bound diffusion coefficient is estimated using a machine learning method.  For the listed polymeric systems and the ultra-conservative assumption, note that the worst-case diffusion coefficient is only defined over a molecular weight range of up to 1100 g/mol.  Therefore, for substances with a molecular weight > 1100 g/mol, the value of the diffusion coefficient assuming a molecular weight of 1100 g/mol is used as a conservative value.  When the machine learning method is used, a check is conducted to verify that the polymer/solute combination falls inside the applicability domain of the model.  If it falls outside that domain, CHRIS instead uses the ultra-conservative assumption.  Additionally, note that polymers with high fractional free volume (FFV) should not be used with the machine learning method because diffusivity may be underestimated.  Instead, the ultra-conservative assumption should be used.
+While these assumptions are typically valid for bulk additives and impurities in biostable polymers, users of CHRIS must confirm conformance to the underlying assumptions or provide supporting justification to ensure compliance for a given system.  CHRIS enables system-specific exposure estimates for fifty-three (53) polymeric systems that are generally biostable (non-swelling and non-degrading).  To estimate chemical release based on the model, the diffusion coefficient of the chemical in the polymer matrix must be specified.  For the fifty-three (53) listed polymeric systems, a worst-case (upper bound) diffusion coefficient, as a function of molecular weight, has been established based on data from the literature.  For polymer matrices that are not included in this list ("Other polymer"), CHRIS has two approaches.  If the polymer glass transition temperature is not specified, an ultra-conservative diffusion coefficient that assumes the polymer has the properties of water is used.  If the glass transition temperature is specified, a less-conservative upper bound diffusion coefficient is estimated using a machine learning method.  For the listed polymeric systems and the ultra-conservative assumption, note that the worst-case diffusion coefficient is only defined over a molecular weight range of up to 1100 g/mol.  Therefore, for substances with a molecular weight > 1100 g/mol, the value of the diffusion coefficient assuming a molecular weight of 1100 g/mol is used as a conservative value.  When the machine learning method is used, a check is conducted to verify that the polymer/solute combination falls inside the applicability domain of the model.  If it falls outside that domain, CHRIS instead uses the ultra-conservative assumption.  Additionally, polymers with high fractional free volume (FFV) should not be used with the machine learning method because the diffusivity may be underestimated.  Instead, the ultra-conservative assumption should be used.
 
 In the absence of adequate toxicological and exposure data for a chemical in a polymeric matrix, a toxicological risk assessment can be conducted for systemic biocompatibility endpoints by comparing the exposure estimate to an appropriate threshold of toxicological concern (TTC).  This is the approach used by CHRIS in this module. The TTC values are based on systemic toxicity, thus CHRIS can address acute systemic toxicity, subacute/subchronic toxicity, genotoxicity, carcinogenicity, and reproductive and developmental toxicity.  It does not, however, address cytotoxicity, sensitization, irritation, hemocompatibility, material mediated pyrogenicity, or implantation. Therefore, an MOS >= 1 implies the chemical will not raise a safety concern with respect to only the systemic biocompatibility endpoints, provided the chemical is not within the cohort of concern, which is reflected in the output of CHRIS. 

exposure3_module/templates/exposure3_index.html

@@ -19,7 +19,7 @@
 </header>
 
 <p><strong>Note: This module only addresses risk associated with the bulk chemicals, excluding color additives, of known initial quantity.
-  For color additives, please use the <a href="/color"> color additive module</a>. </strong></p>
+  For color additives, please use the <a href="/color3"> color additive module</a>. </strong></p>
 
 <p> For details on how to use the CHRIS bulk chemical module, please click the information icons next to each section header and read the
 <a href="{{url_for('.static', filename='exposure_COU.html')}}"> context of use (COU)</a>, which includes limitations of use.