An algae cultivation system may include: a plurality of panels within a cultivation container, positioned along a first axis perpendicular to the gravitational force, wherein a cultivation volume is created between each pair of panels, and wherein the cultivation volumes are fluidly coupled so as to allow horizontal flow therebetween along the first axis; at least one first sparger, to distribute a first fluid into the container at a first operating flow rate; at least one second sparger, to distribute a second fluid into the container at a second operating flow rate; and at least one controller, to control the first operating flow rate and the second operating flow rate. The first operating flow rate may be adapted to allow turbulent mixing the algae in the cultivation container, and the second operating flow rate may be adapted to allow assimilation of materials in a liquid in the cultivation container.

A non-transitory computer-readable storage medium storing a control program for causing a computer to execute for acquiring, from a sensor, multiple monitored values in multistep processes including a process related to fermentation of microbes; setting probability distributions for multiple specific parameters related to unmonitored data and included in multiple parameters included in a nonlinear mathematical model related to the fermentation of the microbes corresponding to the multistep processes; generating monitoring predicted values at next monitoring time of the mathematical model based on the multiple monitored values and the probability distributions; using a distribution of the monitoring predicted values and values monitored at the next monitoring time to update the multiple parameters; and controlling the mathematical model so that errors of the multiple specific parameters generated using the mathematical model including the updated multiple parameters are reduced.

A non-transitory computer-readable storage medium storing a control program for causing a computer to execute for acquiring, from a sensor, multiple monitored values in multistep processes including a process related to fermentation of microbes; setting probability distributions for multiple specific parameters related to unmonitored data and included in multiple parameters included in a nonlinear mathematical model related to the fermentation of the microbes corresponding to the multistep processes; generating monitoring predicted values at next monitoring time of the mathematical model based on the multiple monitored values and the probability distributions; using a distribution of the monitoring predicted values and values monitored at the next monitoring time to update the multiple parameters; and controlling the mathematical model so that errors of the multiple specific parameters generated using the mathematical model including the updated multiple parameters are reduced.

A heating assembly for a bioreactor is disclosed. The heating assembly includes a holder having a plurality of segments coupled to each other to define a unitary structure and a heating component coupled to at least one segment of the plurality of segments. The unitary structure includes a top end, a bottom end, and a side wall. The side wall extends between the top end and the bottom end and along a circumferential direction of the heating assembly to define a cavity. At least a portion of the unitary structure has a gradually varied perimeter along a direction perpendicular to a plane which intersects the side wall and is parallel to the top end and the bottom end.

A heating assembly for a bioreactor is disclosed. The heating assembly includes a holder having a plurality of segments coupled to each other to define a unitary structure and a heating component coupled to at least one segment of the plurality of segments. The unitary structure includes a top end, a bottom end, and a side wall. The side wall extends between the top end and the bottom end and along a circumferential direction of the heating assembly to define a cavity. At least a portion of the unitary structure has a gradually varied perimeter along a direction perpendicular to a plane which intersects the side wall and is parallel to the top end and the bottom end.

Systems, methods, and kits are provided wherein a temperature-sensitive reagent that emits a luminescent signal is used to adjust the identification of the temperature of a sample or to control thermocycling. In various illustrative embodiments, the sample is a PCR mixture.

Systems, methods, and kits are provided wherein a temperature-sensitive reagent that emits a luminescent signal is used to adjust the identification of the temperature of a sample or to control thermocycling. In various illustrative embodiments, the sample is a PCR mixture.

The present application generally pertains to scaling of a production process to produce a chemical, pharmaceutical and/or biotechnological product and/or of a production state of a respective production equipment. Particularly, there is provided a computer-implemented method of scaling a production process to produce a chemical, pharmaceutical and/or biotechnological product, the scaling being from a source scale to a target scale, wherein the production process is defined by a plurality of steps specified by one or more process parameters controlling an execution of the production process, the method comprising: (a) retrieving: parameter evolution information that describes the time evolution of the process parameter(s); a plurality of recipe templates, wherein a recipe comprises the plurality of steps defining the production process, and wherein a recipe template is a recipe in which at least one of the process parameters specifying the plurality of steps is a parameter being variable and having no predetermined value at the outset; (b) receiving: a source setup specification of a source setup to be used for executing the production process at the source scale, the source setup specification comprising the source scale value; a target setup specification of a target setup to be used for executing the production process at the target scale, the target setup specification comprising the target scale value; a source recipe defining the production process at the source scale; at least one acceptability function defining conditions for the values of the process parameter(s) at the source scale and/or at the target scale; (c) simulating the execution of the production process at the source scale using the source setup specification, the source recipe and the parameter evolution information; (d) determining, from the simulation, one or more source trajectories for the process parameter(s), wherein a trajectory corresponds to a time-based profile of values recordable during the simulated execution of the production process; (e) performing a target determination step comprising: selecting a recipe template pertinent to the production process out of the plurality of recipe templates; providing an input value for the at least one variable parameter in the selected recipe template; simulating the execution of the production process at the target scale using the target setup specification, the selected recipe template, the input value for the at least one variable parameter and the parameter evolution information; determining, from the simulation, one or more target trajectories for the process parameters; comparing the source trajectory(ies) and the target trajecto

The present application generally pertains to scaling of a production process to produce a chemical, pharmaceutical and/or biotechnological product and/or of a production state of a respective production equipment. Particularly, there is provided a computer-implemented method of scaling a production process to produce a chemical, pharmaceutical and/or biotechnological product, the scaling being from a source scale to a target scale, wherein the production process is defined by a plurality of steps specified by one or more process parameters controlling an execution of the production process, the method comprising: (a) retrieving: parameter evolution information that describes the time evolution of the process parameter(s); a plurality of recipe templates, wherein a recipe comprises the plurality of steps defining the production process, and wherein a recipe template is a recipe in which at least one of the process parameters specifying the plurality of steps is a parameter being variable and having no predetermined value at the outset; (b) receiving: a source setup specification of a source setup to be used for executing the production process at the source scale, the source setup specification comprising the source scale value; a target setup specification of a target setup to be used for executing the production process at the target scale, the target setup specification comprising the target scale value; a source recipe defining the production process at the source scale; at least one acceptability function defining conditions for the values of the process parameter(s) at the source scale and/or at the target scale; (c) simulating the execution of the production process at the source scale using the source setup specification, the source recipe and the parameter evolution information; (d) determining, from the simulation, one or more source trajectories for the process parameter(s), wherein a trajectory corresponds to a time-based profile of values recordable during the simulated execution of the production process; (e) performing a target determination step comprising: selecting a recipe template pertinent to the production process out of the plurality of recipe templates; providing an input value for the at least one variable parameter in the selected recipe template; simulating the execution of the production process at the target scale using the target setup specification, the selected recipe template, the input value for the at least one variable parameter and the parameter evolution information; determining, from the simulation, one or more target trajectories for the process parameters; comparing the source trajectory(ies) and the target trajecto

Embodiments described herein generally provide for the expansion of cells in a cell expansion system using an active promotion of a coating agent(s) to a cell growth surface in some embodiments. A coating agent may be applied to a surface, such as the cell growth surface of a hollow fiber in a bioreactor, by controlling the movement of a fluid in which a coating agent is suspended, by changing flow rates, by changing flow directions, by rotation of the bioreactor, and/or combinations thereof.