Models to solve problems in drug development was the major theme at Boston QSP’s March event. With over 80 attendees the event featured presentations were made by Jangir Selimkhanov, Ph.D., of Pfizer, Inc. and Jaeyeon Kim, Ph.D., of Merrimack Pharmaceuticals. Both Dr, Selimkhanov and Dr. Kim went into detail on how they used models to address different problems in their research.
Dr. Selimkhanov presented on his current research modeling the relationship between food intake (FI) and body weight (BW) using energy balance models (click here for the slides).
Energy balance is the relationship between energy taken in (food eaten) and the energy out (energy from the food eaten that is used up by the body). The relationship between food intake (FI) and body weight (BW) is known as the FI/BW model.
In his presentation, Dr. Selimkhanov explained that by modeling this relationship and analyzing the data generated, he and his team were able to to predict changes in body weight and food intake when a drug treatment is added.
While the model cannot yet predict the exact drug dose needed to boost the FI/BW relationship, according to Dr. Selimkhanov, the potential that this model could have on treating patients struggling with weight loss and diabetes is still pronounced.
Dr. Kim’s model illustrated how liposomes can be used in cancer therapy treatments. Using nanometer-sized liposome particles to protect the treatment Dr. Kim and his team were able to model how these nanotherapeutics were able to target tumors more accurately than if they were absent. Nanoliposomal irinotecan or nal-IRI is the nanometer-sized liposome used to “drive” the treatment to the cancer cell (the name of this drug is MM-398, also known as Onivyde). Going into his study, three main questions Dr. Kim and his team wanted answered were:
Can the model identify the signals that drive the differentiation activity of a cell?
Can the model utilize mouse-specific outcomes for predictions informing clinical studies?
Can this model be used to figure out the appropriate level of nal-IRI activity needed to attack the cancer cell? In other words, can the model be used to predict how much and how often ?
According to Dr. Kim, the model created “incorporates processes related to PK (pharmacokinetics—how MM-398 is absorbed, distributed, and metabolized in and eliminated from the body), free drug release (where the drug goes), drug metabolism (how MM-398 is broken down and used) and tissue deposition (where the waste goes).”
The findings of this study showed that as the activity of the liposome from the MM-398 injection increased in the cell, the size of the tumor decreased. The model provided crucial information for decision making during translational and clinical studies.
Using a hypothetical ferumoxytol (iron) CT scan, Dr. Kim and his team were also able to model even greater decrease in tumor size if iron were introduced to the tumor associated macrophages near the tumors in the body signaling to the liposome in the MM-398 injection where tumors were.
Following the presentation, the networking reception was hosted at the Venture Café with both Dr. Selimkhanov and Dr. Kim in attendance.
Our next event will be held on May 8th. To attend, please RSVP here.
Thank you the Pfizer for sponsoring the food and beverages at the Boston QSP March event. We would also like to thank our speakers Dr. Jangir Selimkhanov and Dr. Jaeyeon Kim for sharing their research with the Boston QSP community.